Take-home_Ex2: Applied Spatial Interaction Models- A case study of Singapore public bus commuter flows
Setting the Scene
The challenges in urban mobility confront transport operators and city managers. Traditional methods like commuter surveys, despite being costly and time-consuming, have been used to address these questions. However, the delays in cleaning and analyzing survey data often render it outdated by the time reports are ready. The digitization of city-wide infrastructures offers a solution by using data from digital platforms such as GPS and SMART cards.
Currently, although there are a large amount of open data available for public consumption, there are not much research to make use of these data and lack of practical research (using Geospatial Data Science and Analysis) to support policy making decisions.
Objective
Our task for this take-home exercise is to conduct a case study to demonstrate the potential value of GDSA to integrate publicly available data from multiple sources for building a spatial interaction models to determine factors affecting urban mobility patterns of public bus transit.
The Data
Open Government Data
For the purpose of this assignment, data from several open government sources will be used:
Passenger Volume by Origin Destination Bus Stops, Bus Stop Location, Train Station (Feb 2023) and Train Station Exit Point (Aug 2023), just to name a few of them, from LTA DataMall.
Master Plan 2019 Subzone Boundary, HDB Property Information, School Directory and Information and other relevant data from Data.gov.sg.
Specially collected data
- Businesses, retail and services, leisure and recreation, etc geospatial data sets assemble by course instructor.
The Task
The specific tasks of this take-home exercise are as follows:
Geospatial Data Science
Derive an analytical hexagon data of 375m (this distance is the perpendicular distance between the centre of the hexagon and its edges) to represent the traffic analysis zone (TAZ).
With reference to the time intervals provided in the table below, construct an O-D matrix of commuter flows for ONE time interval of our choice by integrating Passenger Volume by Origin Destination Bus Stops and Bus Stop Location from LTA DataMall. The O-D matrix must be aggregated at the analytics hexagon level. I have selected the Weekday Morning Peak for this take home exercise.
Peak hour period Bus tap on time Weekday morning peak (selected) 6am to 9am Weekday afternoon peak 5pm to 8pm Weekend/holiday morning peak 11am to 2pm Weekend/holiday evening peak 4pm to 7pm Display the O-D flows of the passenger trips by using appropriate geovisualisation methods (not more than 5 maps).
Describe the spatial patterns revealed by the geovisualisation (not more than 100 words per visual).
Assemble at least three propulsive and three attractiveness variables by using aspatial and geospatial from publicly available sources.
Compute a distance matrix by using the analytical hexagon data derived earlier.
Spatial Interaction Modelling
Calibrate spatial interactive models to determine factors affecting urban commuting flows at the selected time interval.
Present the modelling results by using appropriate geovisualisation and graphical visualisation methods. (Not more than 5 visuals)
With reference to the Spatial Interaction Model output tables, maps and data visualisation prepared, describe the modelling results. (not more than 100 words per visual).
Getting Started
In this exercise, the following libraries will be used:
sfpackage to perform geoprocessing taskssp package , although an older package, is more efficient for computation of large data.
sfdep package which builds upon
spdeppackage (compute spatial weights matrix and spatially lagged variable for instance..)tmap to create geovisualisations
stplanr for solving common problems in transport planning and modelling, such as how to best get from point A to point B
tidyversethat supports data science, analysis and communication task including creating static statistical graphs.knitrto create html tablesDT library to create interactive html tables
ggpubr for some easy-to-use functions for creating and customizing ‘ggplot2’- based publication ready plots.
performance for for computing measures to assess model quality, which are not directly provided by R’s ‘base’ or ‘stats’ packages. The primary goal of the performance package is to provide utilities for computing indices of model quality and goodness of fit. These include measures like r-squared (R2), root mean squared error (RMSE)
reshape2is an old tool from base R. It handles matrix well for our distance matrix, like pivoting function like
melt(). Tidyverse does not handle matrix very well.ggplot2 to plot graphs
plotly to plot interactive graphs
Importing Data
Aspatial data
Import the Passenger volume by Origin Destination Bus Stops dataset downloaded from the LTA Datamall by using the read_csv() of the readr package.
Check the data fields
Rows: 5,709,512
Columns: 7
$ YEAR_MONTH <chr> "2023-08", "2023-08", "2023-08", "2023-08", "2023-…
$ DAY_TYPE <chr> "WEEKDAY", "WEEKENDS/HOLIDAY", "WEEKENDS/HOLIDAY",…
$ TIME_PER_HOUR <dbl> 16, 16, 14, 14, 17, 17, 17, 17, 7, 17, 14, 10, 10,…
$ PT_TYPE <chr> "BUS", "BUS", "BUS", "BUS", "BUS", "BUS", "BUS", "…
$ ORIGIN_PT_CODE <chr> "04168", "04168", "80119", "80119", "44069", "4406…
$ DESTINATION_PT_CODE <chr> "10051", "10051", "90079", "90079", "17229", "1722…
$ TOTAL_TRIPS <dbl> 7, 2, 3, 10, 5, 4, 3, 22, 3, 3, 7, 1, 3, 1, 3, 1, …Processing the aspatial OD data
The ‘ORIGIN_PT_CODE’ and ‘DESTINATION_PT_CODE’ field is in character field. We will convert it to factor data type.
The function below will extract origin data based on the four time intervals required by the task. The expected arguments are
- daytype: ‘WEEKDAY’ or ‘WEEKENDS/HOLIDAY’
- timeinterval: c(6,8) if we want data from 6am to 9am.
The function will also compute the sum of all trips by ‘ORIGIN_PT_CODE’ for each time interval and stored under a new field called ‘TRIPS’.
Let’s get the data using get_origin function
Take a look at the weekday morning peak dataframe.
Geospatial data
First, we will import the Bus Stop Location shapefiles into R. The output will be a sf point object with 5161 points and 3 fields. As the raw data is in WSG84 geographical coordinate system, we will convert it to EPSG 3414, the projected coordinate system for Singapore.
busstop <- st_read(dsn="data/geospatial/BusStopLocation/BusStopLocation_Jul2023", layer = "BusStop") %>%
st_transform(crs = 3414)Reading layer `BusStop' from data source
`C:\yixin-neo\ISSS624_AGA\Take-home_Ex2\data\geospatial\BusStopLocation\BusStopLocation_Jul2023'
using driver `ESRI Shapefile'
Simple feature collection with 5161 features and 3 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 3970.122 ymin: 26482.1 xmax: 48284.56 ymax: 52983.82
Projected CRS: SVY21Simple feature collection with 5161 features and 3 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 3970.122 ymin: 26482.1 xmax: 48284.56 ymax: 52983.82
Projected CRS: SVY21 / Singapore TM
First 10 features:
BUS_STOP_N BUS_ROOF_N LOC_DESC geometry
1 22069 B06 OPP CEVA LOGISTICS POINT (13576.31 32883.65)
2 32071 B23 AFT TRACK 13 POINT (13228.59 44206.38)
3 44331 B01 BLK 239 POINT (21045.1 40242.08)
4 96081 B05 GRACE INDEPENDENT CH POINT (41603.76 35413.11)
5 11561 B05 BLK 166 POINT (24568.74 30391.85)
6 66191 B03 AFT CORFE PL POINT (30951.58 38079.61)
7 23389 B02A PEC LTD POINT (12476.9 32211.6)
8 54411 B02 BLK 527 POINT (30329.45 39373.92)
9 28531 B09 BLK 536 POINT (14993.31 36905.61)
10 96139 B01 BLK 148 POINT (41642.81 36513.9)Are there any duplicates in ‘BUS_STOP_N’ in busstop?
Checking for duplicates in the ‘BUS_STOP_N’ field reveals that there are about 16 repeated bus stop numbers. Note that they have different geometry points in the simple feature busstop object above. These could be due to temporary bus stops . We should remove these duplicated bus stops number or else it will give us problems when we try to map these bus stops to a grid_id in the Traffic Analysis Zone (TAZ).
busstop %>%
st_drop_geometry() %>%
group_by(BUS_STOP_N) %>%
filter(n()>1) %>%
ungroup() %>%
arrange(BUS_STOP_N)# A tibble: 32 × 3
BUS_STOP_N BUS_ROOF_N LOC_DESC
<chr> <chr> <chr>
1 11009 B04 Ghim Moh Ter
2 11009 B04-TMNL GHIM MOH TER
3 22501 B02 Blk 662A
4 22501 B02 BLK 662A
5 43709 B06 BLK 644
6 43709 B06 BLK 644
7 47201 UNK <NA>
8 47201 NIL W'LANDS NTH STN
9 51071 B21 MACRITCHIE RESERVOIR
10 51071 B21 MACRITCHIE RESERVOIR
# ℹ 22 more rowsTake for instance bus stop number 51071 with two different point geometry values.
Simple feature collection with 1 feature and 3 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 28311.27 ymin: 36036.92 xmax: 28311.27 ymax: 36036.92
Projected CRS: SVY21 / Singapore TM
BUS_STOP_N BUS_ROOF_N LOC_DESC geometry
3470 51071 B21 MACRITCHIE RESERVOIR POINT (28311.27 36036.92)Simple feature collection with 1 feature and 3 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 28282.54 ymin: 36033.93 xmax: 28282.54 ymax: 36033.93
Projected CRS: SVY21 / Singapore TM
BUS_STOP_N BUS_ROOF_N LOC_DESC geometry
3472 51071 B21 MACRITCHIE RESERVOIR POINT (28282.54 36033.93)Removing duplicated bus stops
Double check again that duplicated bus stops have been removed.
busstop %>%
st_drop_geometry() %>%
group_by(BUS_STOP_N) %>%
filter(n()>1) %>%
ungroup() %>%
arrange(BUS_STOP_N)# A tibble: 0 × 3
# ℹ 3 variables: BUS_STOP_N <chr>, BUS_ROOF_N <chr>, LOC_DESC <chr>Further works in this exercise led me to realise that the YISHUN bus interchange is missing from the bus stop location shapefile. It has a postal code of 769100 and using the onemap geocoding function (describe in later section) will give us its SVY21 coordinates of 28314.3933093864, 45511.7310683895. The ‘BUS_STOP_N’ of Yishun Bus interchange is 59009. We will manually add them into the busstop df.
The point in black is to be added
Adding geometry of Yishun Bus Interchange into busstop sf object.
The code chunk below first creates a sf object containing only SVY21 geometry of the Yishun interchange. Next, it appends into the busstop df.
Import the MPSZ-2019 data.
It is a multipolygon sf object with 332 features / subzones/ units.
Reading layer `MPSZ-2019' from data source
`C:\yixin-neo\ISSS624_AGA\Take-home_Ex2\data\geospatial\MPSZ-2019'
using driver `ESRI Shapefile'
Simple feature collection with 332 features and 6 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 103.6057 ymin: 1.158699 xmax: 104.0885 ymax: 1.470775
Geodetic CRS: WGS 84Simple feature collection with 332 features and 6 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 2667.538 ymin: 15748.72 xmax: 56396.44 ymax: 50256.33
Projected CRS: SVY21 / Singapore TM
First 10 features:
SUBZONE_N SUBZONE_C PLN_AREA_N PLN_AREA_C REGION_N
1 MARINA EAST MESZ01 MARINA EAST ME CENTRAL REGION
2 INSTITUTION HILL RVSZ05 RIVER VALLEY RV CENTRAL REGION
3 ROBERTSON QUAY SRSZ01 SINGAPORE RIVER SR CENTRAL REGION
4 JURONG ISLAND AND BUKOM WISZ01 WESTERN ISLANDS WI WEST REGION
5 FORT CANNING MUSZ02 MUSEUM MU CENTRAL REGION
6 MARINA EAST (MP) MPSZ05 MARINE PARADE MP CENTRAL REGION
7 SUDONG WISZ03 WESTERN ISLANDS WI WEST REGION
8 SEMAKAU WISZ02 WESTERN ISLANDS WI WEST REGION
9 SOUTHERN GROUP SISZ02 SOUTHERN ISLANDS SI CENTRAL REGION
10 SENTOSA SISZ01 SOUTHERN ISLANDS SI CENTRAL REGION
REGION_C geometry
1 CR MULTIPOLYGON (((33222.98 29...
2 CR MULTIPOLYGON (((28481.45 30...
3 CR MULTIPOLYGON (((28087.34 30...
4 WR MULTIPOLYGON (((14557.7 304...
5 CR MULTIPOLYGON (((29542.53 31...
6 CR MULTIPOLYGON (((35279.55 30...
7 WR MULTIPOLYGON (((15772.59 21...
8 WR MULTIPOLYGON (((19843.41 21...
9 CR MULTIPOLYGON (((30870.53 22...
10 CR MULTIPOLYGON (((26879.04 26...Creating hexagon layer
Before we can plot the base layer, we have to create hexagonal grids of 375 m (middle to edge) using the mpsz multipolygon sf object using sf.
First , create a grid which the extent equals to the bounding box of the busstop points using st_make_grid().
- To create hexagons of 375m (centre to edge), we should input 750 for ‘cellsize’ parameter. ‘Cellsize’ is defined as the distance from edge to edge.
- Convert to
sfobject and add a unique identifier to each hexagon grid. The output has 834 hexagon units. - Use st_intersects() to count the number of in each hsubzones in each hexagon.
- Filter to retain only hexagons with at least one subzone. The output
bs_counthas 1945 hexagon units.
If we like to, we could save the above hexagon layer to disk.
Read bs_count in R
Reading layer `bs_count_750' from data source
`C:\yixin-neo\ISSS624_AGA\Take-home_Ex2\data\geospatial' using driver `ESRI Shapefile'
Simple feature collection with 834 features and 2 fields
Geometry type: POLYGON
Dimension: XY
Bounding box: xmin: 3595.122 ymin: 26049.09 xmax: 48595.12 ymax: 53545.39
Projected CRS: SVY21 / Singapore TMHow does our hexagon layer look like?
We can see that each hexagon contains a minimum of 1 bus stop and up to a maximum of 19 bus stops.
Geospatial data wrangling
Combining busstop (point sf) and sz_count (polygon sf)
We have to assign a ‘grid_id’ to each bus stops.
The code chunk below performs points and hexagon polygon overlap using st_intersection() and the output will be in sf point object.
Before overlapping:
busstop : 5146 points
bs_count hexagon base layer: 834 hexagons
After overlapping:
busstop_hex : 5165 points suggesting all bus stops falls within at least one hexagon grid. This is good result because we are not losing any bus stops.
busstop_hex <- st_intersection(busstop, bs_count) %>%
select(BUS_STOP_N, LOC_DESC, grid_id, num_bs)
busstop_hexSimple feature collection with 5146 features and 4 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 3970.122 ymin: 26482.1 xmax: 48284.56 ymax: 52983.82
Projected CRS: SVY21 / Singapore TM
First 10 features:
BUS_STOP_N LOC_DESC grid_id num_bs geometry
3261 25059 AFT TUAS STH BLVD 23 1 POINT (3970.122 28063.28)
2565 25751 BEF TUAS STH AVE 14 44 1 POINT (4427.939 28758.67)
254 26379 YONG NAM 46 2 POINT (4473.292 30681.57)
2398 26369 SEE HUP SENG 46 2 POINT (4604.363 31212.96)
2824 25741 HALLIBURTON 66 1 POINT (5060.733 29212.4)
1714 26399 AFT TUAS VIEW CRES 67 4 POINT (5079.51 30214.42)
2822 25719 THE INDEX 67 4 POINT (4799.476 30158.46)
2823 25711 OPP THE INDEX 67 4 POINT (4831.438 30132.43)
4189 26389 BEF TUAS STH AVE 5 67 4 POINT (4776.694 30324.88)
1564 26299 BEF TUAS STH AVE 6 68 1 POINT (4879.489 31948.93)Drop the geometry column of busstop_hex.
busstop_hex_geo <- busstop_hex
busstop_hex <- busstop_hex %>%
st_drop_geometry()
datatable(busstop_hex, class = 'cell-border stripe', options = list(pageLength = 5))Are there duplicates in busstop_hex ?
Let us check for duplicates in busstop_hex df as it will be used to perform a left join later.
The output shows that there are no duplicate rows.
# A tibble: 0 × 4
# ℹ 4 variables: BUS_STOP_N <chr>, LOC_DESC <chr>, grid_id <int>, num_bs <int>Construct an O-D matrix of commuter flows for the morning weekday peak hour
This is how a typical Origin-Destination flow table would look like:
It contains the number of trips between pairs of origin and destination hexagons.
To get the table above, perform left join between day_am and busstop_hex df twice.
First, we append the grid_id from busstop_hex data frame onto day_am data frame. By doing so, we get the fields ‘ORIGIN_GRID_ID’ and ‘ORIGIN_LOC_DESC’ (for tooltip later)from busstop_hex into day_am.
Before join:
day_am : 224,363 rows
After join:
od_data: 224,363 rows
Check for duplicate before proceeding. There are no duplicates.
duplicate <- od_data %>%
group_by_all() %>%
#group_by(ORIGIN_BS, DESTIN_BS) %>%
filter(n()>1) %>%
ungroup()
duplicate# A tibble: 0 × 6
# ℹ 6 variables: ORIGIN_BS <chr>, DESTIN_BS <fct>, TRIPS <dbl>,
# ORIGIN_LOC_DESC <chr>, ORIGIN_GRID_ID <int>, num_bs <int>Next, perform another left join between day_am and busstop_hex df to get the ‘DESTIN_GRID_ID’ and the ‘DESTIN_LOC_DESC’ into day_am df. The number of rows before and after the left joins are the same.
Check for duplicates. The output shows that there are no duplicates.
duplicate <- od_data %>%
group_by_all() %>%
#group_by(ORIGIN_BS, DESTIN_BS) %>%
filter(n()>1) %>%
ungroup()
duplicate# A tibble: 0 × 9
# ℹ 9 variables: ORIGIN_BS <chr>, DESTIN_BS <chr>, TRIPS <dbl>,
# ORIGIN_LOC_DESC <chr>, ORIGIN_GRID_ID <int>, num_bs_origin <int>,
# DESTIN_LOC_DESC <chr>, DESTIN_GRID_ID <int>, num_bs_destin <int>Final clean-up of od_data df.
The code chunk below will do the following:
There are missing grid_ids for some of the origin and destination bus stop because the Bus Stops Location data uploaded by LTA in July 2023 could be more outdated than Passenger Volume by Origin Destination Bus Stops data collected in August 2023. We will drop rows with missing values.
Group-by ‘ORIGIN_GRID_ID’ and ‘DESTIN_GRID_ID’ to generate a new field ‘MORNING_PEAK’ that contains the summation of all trips between each pair of i,j hexagons. (i denotes origin and j denotes destination)
od_datafinally has 62,807 rows.
| ORIGIN_GRID_ID | DESTIN_GRID_ID | MORNING_PEAK | ORIGIN_DESC | DESTIN_DESC |
|---|---|---|---|---|
| 23 | 67 | 1 | AFT TUAS STH BLVD | THE INDEX |
| 23 | 88 | 2 | AFT TUAS STH BLVD | EDGEN MURRAY |
| 23 | 128 | 2 | AFT TUAS STH BLVD | AFT TUAS STH ST 7 |
We will not be visualising the flows at this point in time because we would like to get ‘dist’ between each hexagon for clearer visuslisation later.
Compute Distance Matrix by analytic hexagon level
First as.Spatial() will be used to convert bs_count from sf tibble data frame to SpatialPolygonsDataFrame of sp object as shown in the code chunk below. The reason for doing so is because it is faster to compute distance matrix using sp than sf package.
Next, spDists() of sp package will be used to compute the Euclidean distance between the centroids of the hexagons.
spDists(x, y = x, longlat = FALSE, segments = FALSE, diagonal = FALSE)
spDists returns a full matrix of distances in the metric of the points if longlat=FALSE, or in kilometers if longlat=TRUE; it uses spDistsN1 in case points are two-dimensional. In case of spDists(x,x), it will compute all n x n distances, not the sufficient n x (n-1).
Recall that bs_count contains 834 hexagons and a 834 x 834 distance matrix dist will be created.
We will print out the first 7 rows of the distance matrix. Notice the column and row headers are not labelled by grid_id.
dist <- sp::spDists(bs_count_sp,
longlat = FALSE) # already projected in EPSG:3414
head(dist, n=c(7, 7)) [,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.000 750.000 3269.174 1500.000 2704.163 3968.627 1299.038
[2,] 750.000 0.000 2598.076 750.000 1984.313 3269.174 750.000
[3,] 3269.174 2598.076 0.000 1984.313 750.000 750.000 2704.163
[4,] 1500.000 750.000 1984.313 0.000 1299.038 2598.076 750.000
[5,] 2704.163 1984.313 750.000 1299.038 0.000 1299.038 1984.313
[6,] 3968.627 3269.174 750.000 2598.076 1299.038 0.000 3269.174
[7,] 1299.038 750.000 2704.163 750.000 1984.313 3269.174 0.000Labelling column and row headers of a distance matrix
First, we will create a list sorted according to the the distance matrix by grid_id.
Next we will attach grid_id to row and column for distance matrix matching ahead
grid_id_names <- bs_count$grid_id
colnames(dist) <- paste0(grid_id_names)
rownames(dist) <- paste0(grid_id_names)
dist[1:5,1:5] 23 44 46 66 67
23 0.000 750.000 3269.174 1500.000 2704.163
44 750.000 0.000 2598.076 750.000 1984.313
46 3269.174 2598.076 0.000 1984.313 750.000
66 1500.000 750.000 1984.313 0.000 1299.038
67 2704.163 1984.313 750.000 1299.038 0.000Pivoting distancing value by grid_id
Next, we will pivot the distance matrix into a long table by using the row and column grid_id as show in the code chunk below.
We will use the melt() function of the reshape2 package to convert wide-format data to long-format data. This function will convert wide-format data to a data frame with columns for each combination of row and column indices and their corresponding values.
To do the opposite, used cast().
Var1 Var2 dist
1 23 23 0.000
2 44 23 750.000
3 46 23 3269.174
4 66 23 1500.000
5 67 23 2704.163
6 68 23 3968.627
7 86 23 1299.038
8 87 23 2250.000
9 88 23 3436.932
10 89 23 4683.748There are 695,556 rows in distPair due to 834P2 + 834 = 834 * 833+ 834 possible pairs of hexagon pairs. (Aka the number of possible permutations with replacement)
Three new columns generated, (1) ‘var1’, (2) ‘var2’ and (3) ‘value’ containing the distance for the corresponding hex i -hex j pair; thus rename to ‘dist’
Updating the intra-zonal distances
We will append a constant value to replace the intra-zonal distance of 0.
First, we will remove distance = 0 and find out the minimum value of the inter-zonal distance by using summary().
Var1 Var2 dist
Min. : 23 Min. : 23 Min. : 750
1st Qu.: 871 1st Qu.: 871 1st Qu.: 8352
Median :1324 Median :1324 Median :13332
Mean :1269 Mean :1269 Mean :14162
3rd Qu.:1688 3rd Qu.:1688 3rd Qu.:18929
Max. :2505 Max. :2505 Max. :44680 The minimum inter-hexagon travel was actually 750 m (indicating travelling to adjacent hexagon). If a hexagon’s apothem is 325m (middle to edge), then the length of its long diagonal will be 750m (vertex to opposite vertex).
So we could set the intra-zonal distance to be approximately 300 m.
The code chunk below is used to rename the origin and destination fields.
ORIGIN_GRID_ID DESTIN_GRID_ID dist
1 23 23 300.000
2 44 23 750.000
3 46 23 3269.174
4 66 23 1500.000
5 67 23 2704.163
6 68 23 3968.627Preparing flow data
In this section, our desired output is a dataframe containing number of TRIPS and distance for each origin and destination grid id.
Let us rename the od_data to call it flow_data df. flow_data has 62,807 rows.
flow_data <- od_data %>%
group_by(ORIGIN_GRID_ID, DESTIN_GRID_ID) %>%
summarize(TRIPS = sum(MORNING_PEAK))
head(flow_data) %>% kable()| ORIGIN_GRID_ID | DESTIN_GRID_ID | TRIPS |
|---|---|---|
| 23 | 67 | 1 |
| 23 | 88 | 2 |
| 23 | 128 | 2 |
| 23 | 150 | 1 |
| 23 | 154 | 2 |
| 23 | 175 | 53 |
Separating intra-flow from flow_data df
The code chunk below created two new fields
‘FlowNoIntra’ is a column containing distance = 0 for intra-zonal pairs (diagonals).
‘offset’ is also created.
Filter to keep only inter-zonal trips, removing the intra-zonal trips. After filtering, the number of rows reduced from 62,807 to 62,186 rows.
Rows: 62,186
Columns: 5
Groups: ORIGIN_GRID_ID [817]
$ ORIGIN_GRID_ID <int> 23, 23, 23, 23, 23, 23, 44, 44, 44, 46, 46, 46, 46, 46,…
$ DESTIN_GRID_ID <int> 67, 88, 128, 150, 154, 175, 88, 154, 175, 67, 111, 131,…
$ TRIPS <dbl> 1, 2, 2, 1, 2, 53, 11, 3, 29, 3, 1, 1, 1, 52, 22, 9, 17…
$ FlowNoIntra <dbl> 1, 2, 2, 1, 2, 53, 11, 3, 29, 3, 1, 1, 1, 52, 22, 9, 17…
$ offset <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1…Combining passenger volume data (inter-zone) with distance value
Before we can join inter_zonal_flow and distPair, we need to convert data value type of ‘ORIGIN_SZ’ and’DESTIN_SZ’ fields of inter_zonal_flow and distPair dataframes into factor data type.
Now, left_join() of dplyr will be used to inter_zonal_flow dataframe and distPair dataframe. The output is called flow_data1.
Note
Notes:
distPair is a df containing distances for all corresponding subzone pairs (including self, default to 50m). ‘ORIGIN_GRID_ID’, ‘DESTIN_GRID_ID’, ‘dist’
inter_zonal_flow is a df containing ‘ORIGIN_GRID_ID’, ‘DESTIN_GRID_ID’ and ‘TRIPS’
We will now perform a left join with two sets of join keys.
The output flow_data_1 contains distance and total morning peak trips for each possible pairs of grid-ids (self included).
Before left join:
inter_zonal_flow has 62,186 rows.
distPair has 695,556 rows (is the all possible pairs out of 834 hex grid_ids, order matters and with replacement.)
After join:
flow_data1 has 62,186 rows.
inter_zonal_flow has no distance data. flow_data1 has distance data.
flow_data1 <- inter_zonal_flow %>%
left_join (distPair,
by = c("ORIGIN_GRID_ID" = "ORIGIN_GRID_ID",
"DESTIN_GRID_ID" = "DESTIN_GRID_ID"))
glimpse(flow_data1)Rows: 62,186
Columns: 6
Groups: ORIGIN_GRID_ID [817]
$ ORIGIN_GRID_ID <fct> 23, 23, 23, 23, 23, 23, 44, 44, 44, 46, 46, 46, 46, 46,…
$ DESTIN_GRID_ID <fct> 67, 88, 128, 150, 154, 175, 88, 154, 175, 67, 111, 131,…
$ TRIPS <dbl> 1, 2, 2, 1, 2, 53, 11, 3, 29, 3, 1, 1, 1, 52, 22, 9, 17…
$ FlowNoIntra <dbl> 1, 2, 2, 1, 2, 53, 11, 3, 29, 3, 1, 1, 1, 52, 22, 9, 17…
$ offset <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1…
$ dist <dbl> 2704.163, 3436.932, 1984.313, 2598.076, 6873.864, 7611.…Print out the first 6 rows
Visualising the O-D flows of the weekday morning peak period
Removing intra-zonal flows
We will not plot the intra-zonal flows. The code chunk below will be used to remove intra-zonal flows. It does so by removing the flows that originate and ends in the same subzone.
Rows reduced from 62,807 to 62,186.
Create a flowLine simple feature line object.
In this code chunk below, od2line() of stplanr package is used to create the desired lines.
od_data1 is aspatial while bs_count is geospatial data.
Perform a left join with od_data1 to get ‘ORIGIN_DESC’ and ‘DESTIN_DESC’ information appended into flowLine df. It will be useful for tooltip later when exploring our maps.
We will save flowLine to local disk
Reload flowLine into R.
flowLine contains 62,120 rows but we will only print out trips >= 5,000 in the datatable below.
datatable(flowLine %>%
select(-c(FlowNoIntra, offset)) %>%
filter(TRIPS>=5000),
class = 'cell-border stripe',
options = list(pageLength = 5))Visualisation and Discussion (in Tabset)
In this map, we have filtered trips less than 5000 to make it more manageable to analyse. Thicker line width represents more trips and the length of the lines represents the distance of each inter-hexagonal trip.
We observed that there are some bus routes that carry more passengers. Thick bands appeared at Woodlands Checkpoint area and Boon Lay area. Some routes from North to Eastern Singapore are also longer than usual.
In the next few tabs, we will perform further filtering on ‘TRIPS’ and ‘dist’ and plot interactive maps for us to get the trips details.
Show the code
tmap_mode('plot')
filtered_flowLine <- flowLine %>%
filter(TRIPS >= 5000)
bs_count_filtered <- bs_count %>%
filter(grid_id %in% c(filtered_flowLine$ORIGIN_GRID_ID, filtered_flowLine$DESTIN_GRID_ID))
tm_shape(mpsz) +
tm_polygons(alpha=0.3)+
#col='black') +
#tm_shape(bs_count_filtered) +
#tm_polygons(alpha=0.3) +
filtered_flowLine %>%
tm_shape() +
tm_lines(lwd = 'TRIPS',
style = 'quantile',
scale= c(1, 3, 9, 15, 21, 30),
#scale= c(0.1, 1, 3, 5, 7, 10),
n = 6,
alpha= 0.3,
col='blue') +
tm_view(set.zoom.limits = c(11,17)) +
tm_layout(main.title = 'O-D Flow On Weekday Morning Peak hour' ,
main.title.position = "center",
main.title.size = 2.0,
main.title.fontface = 'bold') +
tm_compass(type="8star", size = 2) +
tm_scale_bar()
In this interactive map, we have filtered and retained the trips >= 15,000, irregardless of the distance of the trip.
Map Tips: Click on the flowline of your interest, it will reveal the number of trips, origin bus stop descriptions and destination bus stop descriptions.
Findings:
1) The flows with the greatest volumes were located near the Woodlands Check Point area that transported commuters across the causeway.
2) Great volumes of flows were associated with destinations at bus or train stations, suggesting that passengers take bus for further transit. This gives us a hint that presence of bus interchange / train stations could be an important explanatory factors for ‘TRIPS’ in our Spatial Interaction Model later.
Show the code
tmap_mode('view')
tmap_options(check.and.fix = TRUE)
filtered_flowLine <- flowLine %>%
filter(TRIPS >= 15000)
bs_count_filtered <- bs_count %>%
filter(grid_id %in% c(filtered_flowLine$ORIGIN_GRID_ID, filtered_flowLine$DESTIN_GRID_ID))
tm_shape(mpsz) +
tm_polygons(alpha=0.7,
col='black') +
tm_shape(bs_count_filtered) +
tm_polygons(alpha=0.4) +
#tm_shape(busstop_hex_geo) +
#tm_dots(size= 0.005)+
filtered_flowLine %>%
tm_shape() +
tm_lines(lwd = 'TRIPS',
style = 'quantile',
scale=c(4,5,6,7,8,9),
#scale= c(1, 3, 9, 15, 21, 30),
#scale= c(0.1, 1, 3, 5, 7, 10),
n = 6,
alpha= 0.5,
popup.vars=c("# Trips:"="TRIPS",
"Orig Desc:"="ORIGIN_DESC",
"Destin Desc:" = "DESTIN_DESC",
"Distance:" = 'dist'),
col='yellow') +
tm_view(set.zoom.limits = c(11,17)) +
tm_layout(main.title = 'O-D Flow On Weekday Morning Peak hour' ,
main.title.size = 1.0,
main.title.fontface = 'bold')In order to investigate the long distance bus trips with considerable amount of trips volume, we have filtered and retain TRIPS >= 5000 and distance >= 13km. We noticed that these trips tend to connect passengers between the Northern parts of Singapore (Woodlands, Khatib and Yishun for instance) and the Eastern parts of Singapore (Tampanies, Seng Kang and Punggol for instance). Taking a look at the Singapore MRT map, it would require passengers to use at least three different ‘lines’ in order for them to commute between Eastern and Northern Singapore; maybe this is why passengers prefer to take a direct bus instead.
Show the code
tmap_mode('view')
tmap_options(check.and.fix = TRUE)
filtered_flowLine <- flowLine %>%
filter(dist >= 13000,
TRIPS >= 5000)
bs_count_filtered <- bs_count %>%
filter(grid_id %in% c(filtered_flowLine$ORIGIN_GRID_ID, filtered_flowLine$DESTIN_GRID_ID))
tm_shape(mpsz) +
tm_polygons(alpha=0.7,
col='black') +
tm_shape(bs_count_filtered) +
tm_polygons(alpha=0.4) +
#tm_shape(busstop_hex_geo) +
#tm_dots(size= 0.005)+
filtered_flowLine %>%
tm_shape() +
tm_lines(lwd = 'TRIPS',
style = 'quantile',
scale=c(4,5,6,7,8,9),
#scale= c(1, 3, 9, 15, 21, 30),
#scale= c(0.1, 1, 3, 5, 7, 10),
n = 6,
alpha= 0.5,
popup.vars=c("# Trips:"="TRIPS",
"Orig Desc:"="ORIGIN_DESC",
"Destin Desc:" = "DESTIN_DESC",
"Distance:" = 'dist'),
col='yellow') +
tm_view(set.zoom.limits = c(11,17)) +
tm_layout(main.title = 'O-D Flow On Weekday Morning Peak hour' ,
main.title.size = 1.0,
main.title.fontface = 'bold')For our curiosity of the longest bus route, we filter all trips with distances >= 23 km irregardless of trips volume.
Some passengers were willing to take bus between Changi Airport and Woodlands Checkpoint and also between Bedok and Boon Lay.
Zoom in and click on the flowlines for details on trip volume, distance and bus stop details!
Show the code
tmap_mode('view')
tmap_options(check.and.fix = TRUE)
filtered_flowLine <- flowLine %>%
filter(dist >= 23000)
bs_count_filtered <- bs_count %>%
filter(grid_id %in% c(filtered_flowLine$ORIGIN_GRID_ID, filtered_flowLine$DESTIN_GRID_ID))
tm_shape(mpsz) +
tm_polygons(alpha=0.7,
col='black') +
tm_shape(bs_count_filtered) +
tm_polygons(alpha=0.4) +
#tm_shape(busstop_hex_geo) +
#tm_dots(size= 0.005)+
filtered_flowLine %>%
tm_shape() +
tm_lines(lwd = 'TRIPS',
style = 'quantile',
scale=c(4,5,6,7,8,9),
#scale= c(1, 3, 9, 15, 21, 30),
#scale= c(0.1, 1, 3, 5, 7, 10),
n = 6,
alpha= 0.5,
popup.vars=c("# Trips:"="TRIPS",
"Orig Desc:"="ORIGIN_DESC",
"Destin Desc:" = "DESTIN_DESC",
"Distance:" = 'dist'),
col='yellow') +
tm_view(set.zoom.limits = c(11,17)) +
tm_layout(main.title = 'O-D Flow On Weekday Morning Peak hour' ,
main.title.size = 1.0,
main.title.fontface = 'bold')Preparing Origin and Destination Attributes
Importing the attractiveness and propulsive geospatial data
Geospatial dataset 1
Train_Station_Exit_Layer shapefile downloaded from LTA data mall. It contains point coordinates of station box exits. The train station exits are potentially one of the attractiveness of destinations as bus passengers could take bus to MRT stations for transfer.
train_exit <- st_read(dsn='data/geospatial',
layer='Train_Station_Exit_Layer') %>%
st_transform(crs=3414)Reading layer `Train_Station_Exit_Layer' from data source
`C:\yixin-neo\ISSS624_AGA\Take-home_Ex2\data\geospatial' using driver `ESRI Shapefile'
Simple feature collection with 565 features and 2 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 6134.086 ymin: 27499.7 xmax: 45356.36 ymax: 47865.92
Projected CRS: SVY21The file contains duplicated ‘stn_name’ and ‘exit_code’ fields.
Simple feature collection with 17 features and 2 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 18072.23 ymin: 27512.2 xmax: 42314.55 ymax: 40853.37
Projected CRS: SVY21 / Singapore TM
# A tibble: 17 × 3
stn_name exit_code geometry
<chr> <chr> <POINT [m]>
1 BUKIT PANJANG MRT STATION Exit A (20054.56 40109.33)
2 CHOA CHU KANG MRT STATION Exit D (18084.87 40849.96)
3 HARBOURFRONT MRT STATION Exit A (26569.87 27614.83)
4 EXPO MRT STATION Exit A (42314.55 35278.98)
5 HARBOURFRONT MRT STATION Exit A (26797.06 27512.2)
6 CHOA CHU KANG MRT STATION Exit C (18117.61 40853.37)
7 CHOA CHU KANG MRT STATION Exit A (18121.99 40819.65)
8 BUKIT PANJANG MRT STATION Exit A (19795.81 40301.42)
9 UPPER CHANGI MRT STATION Exit A (42246.13 36002.08)
10 UPPER CHANGI MRT STATION Exit A (42205.19 36018.15)
11 BEDOK NORTH MRT STATION Exit B (37542.44 35150.99)
12 BEDOK NORTH MRT STATION Exit B (37550.39 35173.81)
13 BUKIT PANJANG MRT STATION Exit A (20066.96 40082.6)
14 CHOA CHU KANG MRT STATION Exit A (18122.31 40816.19)
15 CHOA CHU KANG MRT STATION Exit C (18112.29 40852.68)
16 CHOA CHU KANG MRT STATION Exit D (18072.23 40812.88)
17 EXPO MRT STATION Exit A (42302.73 35296.8)Remove the duplicates and check that all duplicates are removed. 556 rows remaining.
train_exit <- train_exit %>%
distinct(stn_name,
exit_code,
.keep_all = TRUE)
train_exit %>%
group_by(stn_name, exit_code) %>%
filter(n()>1) %>%
ungroup()Simple feature collection with 0 features and 2 fields
Bounding box: xmin: NA ymin: NA xmax: NA ymax: NA
Projected CRS: SVY21 / Singapore TM
# A tibble: 0 × 3
# ℹ 3 variables: stn_name <chr>, exit_code <chr>, geometry <GEOMETRY [m]>Count the number of station exits within each hexagon and then also, assign ‘grid_id’ to each train station exits points. The bs_count df is now enriched with number of mrt station exits information!
bs_count$train_exit_ct = lengths(st_intersects(bs_count,train_exit))
bs_count %>% arrange(desc(train_exit_ct)) %>% head()Simple feature collection with 6 features and 3 fields
Geometry type: POLYGON
Dimension: XY
Bounding box: xmin: 27595.12 ymin: 28647.16 xmax: 30595.12 ymax: 32111.27
Projected CRS: SVY21 / Singapore TM
grid_id num_bs train_exit_ct geometry
1 1370 7 13 POLYGON ((27970.12 31245.24...
2 1452 10 13 POLYGON ((29470.12 28647.16...
3 1473 8 12 POLYGON ((29845.12 29296.68...
4 1494 5 12 POLYGON ((30220.12 28647.16...
5 1495 10 10 POLYGON ((30220.12 29946.2,...
6 1474 16 9 POLYGON ((29845.12 30595.72...Lets take a look at the train station exits points (denoted by the black dots). The red hexagons highlights the grids with more than 10 train stations exits.
Show the code
tmap_mode('plot')
tmap_options(check.and.fix = TRUE)
tm_shape(mpsz)+
tm_polygons(alpha=0.3) +
tm_shape(bs_count[bs_count$train_exit_ct >=10,]) +
tm_polygons(alpha = 0.3,
col='red') +
tm_shape(train_exit) +
tm_dots(size=0.01) +
tm_layout(main.title = "Train exits location",
main.title.fontface = 'bold',
main.title.position = "center",
main.title.size = 2,
legend.height = 0.45,
legend.width = 0.35,
frame = TRUE) +
tm_view(set.zoom.limits = c(11,16)) +
tm_compass(type="8star", size = 2) +
tm_scale_bar()
Let us continue to import more origin and destination attributes data.
Geospatial dataset 2
We will import Pre-Schools Locations kml file from data.gov.sg. It is a POINT sf object. This variable is potentially one of the attractiveness of our destinations.
preschool = st_read('data/geospatial/pre-schools-location-kml.kml') %>%
st_transform(preschool, crs=3414)Reading layer `PRESCHOOLS_LOCATION' from data source
`C:\yixin-neo\ISSS624_AGA\Take-home_Ex2\data\geospatial\pre-schools-location-kml.kml'
using driver `KML'
Simple feature collection with 1925 features and 2 fields
Geometry type: POINT
Dimension: XYZ
Bounding box: xmin: 103.6824 ymin: 1.247759 xmax: 103.9897 ymax: 1.462134
z_range: zmin: 0 zmax: 0
Geodetic CRS: WGS 84Count the number of preschools within each hexagon and then also, assign ‘grid_id’ to each preschool. The bs_count df is now enriched with number of preschool information!
Let us take a look at the preschool locations (denoted by the black dots). The red hexagons highlights the grids with more than 10 preschools.
Show the code
tmap_mode('plot')
tmap_options(check.and.fix = TRUE)
tm_shape(mpsz)+
tm_polygons(alpha=0.3) +
tm_shape(bs_count[bs_count$preschool_ct >= 10,]) +
tm_polygons(alpha = 0.3,
col='red') +
tm_shape(preschool) +
tm_dots(size=0.01) +
tm_layout(main.title = "Preschool location",
main.title.fontface = 'bold',
main.title.position = "center",
main.title.size = 2,
legend.height = 0.45,
legend.width = 0.35,
frame = TRUE) +
tm_view(set.zoom.limits = c(11,16)) +
tm_compass(type="8star", size = 2) +
tm_scale_bar()
Geospatial dataset 3
We will import the Business shape file provided by Prof Kam. It is a POINT sf object containing information about business locations in Singapore. This variable is potentially one of the attractiveness of our destinations because passengers could take bus to work during the morning peak period.
Reading layer `Business' from data source
`C:\yixin-neo\ISSS624_AGA\Take-home_Ex2\data\geospatial' using driver `ESRI Shapefile'
Simple feature collection with 6550 features and 3 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 3669.148 ymin: 25408.41 xmax: 47034.83 ymax: 50148.54
Projected CRS: SVY21 / Singapore TMCount the number of businesses within each hexagon and then also, assign ‘grid_id’ to each businesses. The bs_count df is now enriched with business POI!
Let us take a look at the business locations (denoted by the black dots). The red hexagons highlights the grids with more than 50 business POI. We observe that business locations are more concentrated on the Southern parts of Singapore.
Show the code
tmap_mode('plot')
tmap_options(check.and.fix = TRUE)
tm_shape(mpsz)+
tm_polygons(alpha=0.3) +
tm_shape(bs_count[bs_count$business_ct >= 50,]) +
tm_polygons(alpha = 0.3,
col='red') +
tm_shape(business) +
tm_dots(size=0.01) +
tm_layout(main.title = "Business location",
main.title.fontface = 'bold',
main.title.position = "center",
main.title.size = 2,
legend.height = 0.45,
legend.width = 0.35,
frame = TRUE) +
tm_view(set.zoom.limits = c(11,16)) +
tm_compass(type="8star", size = 2) +
tm_scale_bar()
Geospatial dataset 4
We will import the FinServ shape file provided by Prof Kam. It is a POINT sf object containing information about financial service locations (Banks / Money Changers) in Singapore. This variable is potentially one of the attractiveness of our destinations because passengers could take bus to work during the morning peak period.
Reading layer `FinServ' from data source
`C:\yixin-neo\ISSS624_AGA\Take-home_Ex2\data\geospatial' using driver `ESRI Shapefile'
Simple feature collection with 3320 features and 3 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 4881.527 ymin: 25171.88 xmax: 46526.16 ymax: 49338.02
Projected CRS: SVY21 / Singapore TMCount the number of financial service points within each hexagon and then also, assign ‘grid_id’ to each financial service points. The bs_count df is now enriched with financial services information!
Let us take a look at the financial services locations (denoted by the black dots). The red hexagons highlights the grids with more than 50 financial services points. The financial services are most concentrated at the CBD district.
Show the code
tmap_mode('plot')
tmap_options(check.and.fix = TRUE)
tm_shape(mpsz)+
tm_polygons(alpha=0.3) +
tm_shape(bs_count[bs_count$finserv_ct >= 50,]) +
tm_polygons(alpha = 0.3,
col='red') +
tm_shape(finserv) +
tm_dots(size=0.01) +
tm_layout(main.title = "Financial Service location",
main.title.fontface = 'bold',
main.title.position = "center",
main.title.size = 2,
legend.height = 0.45,
legend.width = 0.35,
frame = TRUE) +
tm_view(set.zoom.limits = c(11,16)) +
tm_compass(type="8star", size = 2) +
tm_scale_bar()
Importing the attractiveness and propulsive aspatial data
Aspatial dataset 1
Let us import the Schools general information in csv format , downloaded from School Directory and Information from data.gov.sg. It contains location (implicitly in the form of the field ‘POSTAL_CODE’) of the MOE kindergartens, Primary Schools , Secondary Schools and junior colleges. It does not contain ITEs , Polytechnics and Universities locations. There is a total of 346 records inside this csv file.
| school_name | url_address | address | postal_code | telephone_no | telephone_no_2 | fax_no | fax_no_2 | email_address | mrt_desc | bus_desc | principal_name | first_vp_name | second_vp_name | third_vp_name | fourth_vp_name | fifth_vp_name | sixth_vp_name | dgp_code | zone_code | type_code | nature_code | session_code | mainlevel_code | sap_ind | autonomous_ind | gifted_ind | ip_ind | mothertongue1_code | mothertongue2_code | mothertongue3_code |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ADMIRALTY PRIMARY SCHOOL | https://admiraltypri.moe.edu.sg/ | 11 WOODLANDS CIRCLE | 738907 | 63620598 | na | 63627512 | na | ADMIRALTY_PS@MOE.EDU.SG | Admiralty Station | TIBS 965, 964, 913 | MR PEK WEE HAUR | MDM CHUA MUI LING | MDM NUR SABARIAH BTE MOHD IBRAHIM | NULL | NULL | NULL | NULL | WOODLANDS | NORTH | GOVERNMENT SCHOOL | CO-ED SCHOOL | FULL DAY | PRIMARY | No | No | No | No | Chinese | Malay | Tamil |
| ADMIRALTY SECONDARY SCHOOL | http://www.admiraltysec.moe.edu.sg | 31 WOODLANDS CRESCENT | 737916 | 63651733 | 63654596 | 63652774 | na | Admiralty_SS@moe.edu.sg | ADMIRALTY MRT | 904 | MR LAM YUI- P’NG | MR NG SONG LIM STEVEN | MR SHEIK ALAUDIN B MOHD ISMAIL | NULL | NULL | NULL | NULL | WOODLANDS | NORTH | GOVERNMENT SCHOOL | CO-ED SCHOOL | SINGLE SESSION | SECONDARY | No | No | No | No | Chinese | Malay | Tamil |
| AHMAD IBRAHIM PRIMARY SCHOOL | http://www.ahmadibrahimpri.moe.edu.sg | 10 YISHUN STREET 11 | 768643 | 67592906 | na | 67592927 | na | aips@moe.edu.sg | Yishun | Yishun Ring Road - 812 (white plate); Yishun Ave 2 - 169, 804, 965, 117, 883 | MISS ONG LEE CHOO | MADAM SULASNI BINTE ABDUL RAHMAN | NULL | NULL | NULL | NULL | NULL | YISHUN | NORTH | GOVERNMENT SCHOOL | CO-ED SCHOOL | SINGLE SESSION | PRIMARY | No | No | No | No | Chinese | Malay | Tamil |
| AHMAD IBRAHIM SECONDARY SCHOOL | http://www.ahmadibrahimsec.moe.edu.sg | 751 YISHUN AVENUE 7 | 768928 | 67585384 | na | 67557778 | na | aiss@moe.edu.sg | CANBERRA MRT, YISHUN MRT | 117, 167, 169, 800, 811, 812, 883, 856, 858, 859, 965, 969, 980 | MISS TAN KE XIN | MR YAO ZHIXUAN TERENCE | MISS LEA SHU HUI | NULL | NULL | NULL | NULL | YISHUN | NORTH | GOVERNMENT SCHOOL | CO-ED SCHOOL | SINGLE SESSION | SECONDARY | No | No | No | No | Chinese | Malay | Tamil |
| AI TONG SCHOOL | http://www.aitong.moe.edu.sg | 100 Bright Hill Drive | 579646 | 64547672 | na | 64532726 | na | AITONG_SCH@MOE.EDU.SG | Bishan MRT | 410, 162, 52 | MDM GOH LING LING DIANE | MDM NG BEE ENG, CINDY | MR YAK BENG WEI | NULL | NULL | NULL | NULL | BISHAN | SOUTH | GOVERNMENT-AIDED SCH | CO-ED SCHOOL | SINGLE SESSION | PRIMARY | Yes | No | No | No | Chinese | na | na |
| ALEXANDRA PRIMARY SCHOOL | http://alexandrapri.moe.edu.sg | 2A Prince Charles Crescent | 159016 | 62485400 | na | 62485409 | na | alexandra_ps@moe.edu.sg | Redhill Station Tiong Bahru Station | 51, 122, 139, 186, 970. | MDM TEO CHING LING | MDM NORAINI BTE MANSOOR | NULL | NULL | NULL | NULL | NULL | BUKIT MERAH | SOUTH | GOVERNMENT SCHOOL | CO-ED SCHOOL | SINGLE SESSION | PRIMARY | No | No | No | No | Chinese | Malay | Tamil |
Next, we will load poly_ite_postal csv file that is collated by myself. It contains the postal codes of the 5 polytechnics and the 3 ITE colleges in Singapore.
| school_name | postal_code |
|---|---|
| Singapore Polytechnic | 139651 |
| Republic Polytechnic | 738964 |
| Nanyang Polytechnic | 569830 |
| Temasek Polytechnic | 529757 |
| Ngee Ann Polytechnic | 599489 |
| ITE Central | 567720 |
| ITE Colleage East | 486047 |
| ITE College West | 688236 |
Since there are only 8 records of ITEs and Polys, I have manually added these 8 records into the original Generalinformationofschools.csv above and rename it as allsch.csv
Reload the allsch.csv, which contains 354 records in total.
Geocoding the schools location
We will use the OneMap API to retrieve the longitude (X) and latitude (Y) coordinates using the ‘POSTAL_CODE’ field. First load the httr package which works in a TIDY manner.
OneMap API is owned by SLA. The API documentation is found here.
The code chunk below does the following:
- Initiate two empty dataframes;
foundto contain the results of the postal codes that are successful geocoded andnot_foundto contain the postal codes that are not successfully geocoded. - Uses a loop to use the OneMap API for
schandterdf.
found <- data.frame()
not_found <- data.frame()
for(postcode in postcodes) {
query <- list('searchVal' = postcode, 'returnGeom' = 'Y', 'getAddrDetails' = 'Y', 'pageNum' = '1')
res <- GET(url, query=query)
if((content(res)$found)!=0){
found<-rbind(found, data.frame(content(res))[4:13])
} else{
not_found = data.frame(postcode)
}
}Out of the 354 records in allsch, 1 school (Zhenghua Secondary School) is unsuccessfully geocoded.
Let us merge the output of geocoding with the original allsch.csv file.
Write merged into a csv file and manually add the longitude and latitude (1.3887, 103.7652 ) of Zhenghua Secondary into the csv file.
After manual edit, reload the schools_geocoded.csv file in R.
Convert sch to sf point object with longitude and latitude
Convert to SVY21 Singapore Projected Coordinates System after converting to sf object.
Count the number of schools in each hexagon and assign each school to a grid_id.
bs_count$sch_ct = lengths(st_intersects(bs_count,sch_sf))
bs_count %>% arrange(desc(sch_ct)) %>% head()Simple feature collection with 6 features and 7 fields
Geometry type: POLYGON
Dimension: XY
Bounding box: xmin: 15220.12 ymin: 31894.76 xmax: 37720.12 ymax: 42503.57
Projected CRS: SVY21 / Singapore TM
grid_id num_bs train_exit_ct preschool_ct business_ct finserv_ct sch_ct
1 873 1 0 2 0 0 4
2 1350 4 1 2 0 1 4
3 1895 11 0 1 0 1 4
4 680 9 3 2 0 5 3
5 786 11 0 3 0 1 3
6 832 11 4 10 0 12 3
geometry
1 POLYGON ((18970.12 40338.51...
2 POLYGON ((27595.12 33193.8,...
3 POLYGON ((37345.12 31894.76...
4 POLYGON ((15595.12 35791.87...
5 POLYGON ((17470.12 36441.39...
6 POLYGON ((18220.12 41637.55...Let us take a look at the map. The highest count of schools in a hexagon is 4.
Show the code
tmap_mode('plot')
tmap_options(check.and.fix = TRUE)
tm_shape(mpsz)+
tm_polygons(alpha=0.3) +
tm_shape(bs_count[bs_count$sch_ct>=4,]) +
tm_polygons(alpha = 0.3,
col = 'red') +
tm_shape(sch_sf) +
tm_dots() +
tm_layout(main.title = "Schools location",
main.title.fontface = 'bold',
main.title.position = "center",
main.title.size = 2,
legend.height = 0.45,
legend.width = 0.35,
frame = TRUE) +
tm_view(set.zoom.limits = c(11,16)) +
tm_compass(type="8star", size = 2) +
tm_scale_bar()
Aspatial dataset 2
We will now import the hdb.csv file provided by Prof Kam. The original source file is named HDB Property Information downloaded from this link, but it contains no postal code or coordinates. it contains data from Jan 1937 - Jun 2023.
The hdb.csv used in this exercise has been geocoded by Prof Kam. It contains information postal code and longitude/ latitude coordinates.
We will not be using commercial HDB property, therefore we will remove non-residential rows. The number of rows reduced from 12,442 to to 10,181.
The fields ‘total_rental_ct’ refers to the estimated number of people who stay in rented apartments, ‘total_nroom_ct’ refers to the estimated number of people staying in n-room apartment and ‘total_owner_ct’ refers to the estimated number of residents who stay in HDB property.
The reason for retaining the details of n-room count is because it is a potential proxy for income level. The multipliers for each room type (eg. 1 for 1 room, 2 for 2 rooms, 10 for 3 rooms for instance) is estimated using the HDBResidentPopulationAged15YearsandAbovebyFlatType.csv retrieved from data.gov. The bar chart below will show how the multipliers were estimated.
Show the code
ggplot(res_est, aes(x = flat_type, y = number)) +
geom_bar(stat = "identity") +
geom_text(aes(label = paste0(number,', ', round(number/sum(number)*100,1), '%')),
position = position_dodge(width = 0.8), vjust= -1, size = 3.5) +
labs(title = "Number of residents by Flat Types",
x = "Flat Type",
y = "Number") +
theme(plot.title = element_text(face="bold"))
hdb <- read_csv('data/aspatial/hdb.csv') %>%
filter(residential == "Y") %>%
mutate(total_rental_ct = `1room_rental`*1 + `2room_rental`*2 + `3room_rental`*3 + `other_room_rental`*4,
total_1room_ct = `1room_sold`,
total_2room_ct = `2room_sold`*2,
total_3room_ct = `3room_sold`*10,
total_4room_ct = `4room_sold`*21,
total_5room_ct = `5room_sold`*13,
total_exec_ct = `exec_sold`*4,
total_multi_ct = `multigen_sold`*13,
total_studio_ct = `studio_apartment_sold`,
total_owner_ct = `1room_sold`*1 + `2room_sold`*2 + `3room_sold`*10 + `4room_sold`*21 + `5room_sold`*13 + `exec_sold`*4 + `multigen_sold`*13 + `studio_apartment_sold`*1) %>%
select(blk_no, street, total_rental_ct, total_1room_ct, total_1room_ct,total_2room_ct,total_3room_ct,total_4room_ct,total_5room_ct,total_exec_ct,total_multi_ct, total_studio_ct,total_owner_ct, lat, lng)Let us take a look at the first six rows of hdb df.
| blk_no | street | total_rental_ct | total_1room_ct | total_2room_ct | total_3room_ct | total_4room_ct | total_5room_ct | total_exec_ct | total_multi_ct | total_studio_ct | total_owner_ct | lat | lng |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | BEACH RD | 0 | 0 | 2 | 1380 | 21 | 26 | 0 | 0 | 0 | 1429 | 1.295097 | 103.8541 |
| 1 | BEDOK STH AVE 1 | 0 | 0 | 0 | 2040 | 0 | 26 | 0 | 0 | 0 | 2066 | 1.320852 | 103.9337 |
| 1 | CHAI CHEE RD | 0 | 0 | 0 | 0 | 210 | 1196 | 0 | 0 | 0 | 1406 | 1.327969 | 103.9227 |
| 1 | CHANGI VILLAGE RD | 0 | 0 | 0 | 540 | 0 | 13 | 0 | 0 | 0 | 553 | 1.388610 | 103.9881 |
| 1 | DELTA AVE | 0 | 0 | 0 | 0 | 0 | 1248 | 0 | 0 | 0 | 1248 | 1.292075 | 103.8286 |
| 1 | DOVER RD | 0 | 0 | 0 | 1180 | 0 | 91 | 0 | 0 | 0 | 1271 | 1.302530 | 103.7833 |
Tranform hdb to a simply feature POINT object using st_as_sf function and transform from WSG84 to SVY21 Singapore Projected Coordinate System using st_transform() of sf package.
Simple feature collection with 10181 features and 12 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 11519.15 ymin: 28097.64 xmax: 45224.46 ymax: 48741.06
Projected CRS: SVY21 / Singapore TM
# A tibble: 10,181 × 13
blk_no street total_rental_ct total_1room_ct total_2room_ct total_3room_ct
* <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 1 BEACH RD 0 0 2 1380
2 1 BEDOK ST… 0 0 0 2040
3 1 CHAI CHE… 0 0 0 0
4 1 CHANGI V… 0 0 0 540
5 1 DELTA AVE 0 0 0 0
6 1 DOVER RD 0 0 0 1180
7 1 EUNOS CR… 494 0 0 0
8 1 EVERTON … 0 0 0 620
9 1 GHIM MOH… 0 0 0 2160
10 1 HAIG RD 0 0 0 2140
# ℹ 10,171 more rows
# ℹ 7 more variables: total_4room_ct <dbl>, total_5room_ct <dbl>,
# total_exec_ct <dbl>, total_multi_ct <dbl>, total_studio_ct <dbl>,
# total_owner_ct <dbl>, geometry <POINT [m]>Assign a ‘grid_id’ to each observation inside the hdb_sf POINT sf object by using the st_intersection() function.
Before: hdb_sf contains 10,181 rows
After: st_intersection(): hdb_hex contains 10,133 rows. Some points in hdb_sf do not fall within bs_count basic hexagon units. This is expected as bs_count that does not have hexagons with zero bus stop counts.
Drop the geometry column, and check for duplicates.
# A tibble: 0 × 19
# ℹ 19 variables: blk_no <chr>, street <chr>, total_rental_ct <dbl>,
# total_1room_ct <dbl>, total_2room_ct <dbl>, total_3room_ct <dbl>,
# total_4room_ct <dbl>, total_5room_ct <dbl>, total_exec_ct <dbl>,
# total_multi_ct <dbl>, total_studio_ct <dbl>, total_owner_ct <dbl>,
# grid_id <int>, num_bs <int>, train_exit_ct <int>, preschool_ct <int>,
# business_ct <int>, finserv_ct <int>, sch_ct <int>For each ‘grid_id’, sum the ‘total_rental_ct’ and ‘total_owners_ct’. After group_by, the number of rows reduced from 10,133 to 392 unique ‘grid_id’
hdb_hex <- hdb_hex %>%
group_by(grid_id) %>%
summarise(hdb_rental_ct = sum(total_rental_ct),
hdb_1room_ct = sum(total_1room_ct),
hdb_2room_ct = sum(total_2room_ct),
hdb_3room_ct = sum(total_3room_ct),
hdb_4room_ct = sum(total_4room_ct),
hdb_5room_ct = sum(total_5room_ct),
hdb_exec_ct = sum(total_exec_ct),
hdb_multi_ct = sum(total_multi_ct),
hdb_studio_ct = sum(total_studio_ct),
hdb_owner_ct = sum (total_owner_ct)) %>%
ungroup()Append the HDB rental and owner counts to the bs_count df by performing a left join
bs_count <- left_join(bs_count, hdb_hex,
by= c('grid_id' = 'grid_id'))
bs_count<- bs_count %>%
mutate(hdb_rental_ct = replace_na(hdb_rental_ct, 0),
hdb_1room_ct = replace_na(hdb_1room_ct, 0),
hdb_2room_ct = replace_na(hdb_2room_ct, 0),
hdb_3room_ct = replace_na(hdb_3room_ct, 0),
hdb_4room_ct = replace_na(hdb_4room_ct, 0),
hdb_5room_ct = replace_na(hdb_5room_ct, 0),
hdb_exec_ct = replace_na(hdb_exec_ct, 0),
hdb_multi_ct = replace_na(hdb_multi_ct, 0),
hdb_studio_ct = replace_na(hdb_studio_ct, 0),
hdb_owner_ct = replace_na(hdb_owner_ct, 0))Let us visualise the estimated population density of Singapore residents who stays in HDB property.
Show the code
tmap_mode('plot')
tmap_options(check.and.fix = TRUE)
tm_shape(mpsz)+
tm_polygons(alpha=0.3) +
tm_shape(bs_count) +
tm_fill('hdb_owner_ct',
alpha= 0.7) +
tm_borders(col='grey') +
tm_layout(main.title = "Population density of HDB residents 2023 by Hexagon",
main.title.fontface = 'bold',
main.title.position = "center",
main.title.size = 2,
legend.height = 0.55,
legend.width = 0.45,
frame = TRUE) +
tm_compass(type="8star", size = 2) +
tm_scale_bar()
This rough estimation of the population density of residents staying in HDB (until June 2023) is acceptable because according to Singapore Census of Population 2020, the top four planning areas with more than 250,000 residents are Bedok, Jurong West, Tampanies and Woodlands. (see chart below). The level of intensity of the map above looks similar to the intensity of the map below, with the exception of the North_east area. The North-East region with planning areas like Punggol and Seng Kang are newer estates that are probably not captured in 2020 census.
Append all attributes to flow_data1 df
We will perform left_join() twice to get the origin and destination attributes properly appended into the flow_data1 df (currently contains only response variable ‘TRIPS’ and one explanatory variable ‘dist’) .
First, convert ‘grid_id’ in sz_count to factor format.
flow_data1 <- flow_data1 %>%
left_join(bs_count,
by = c('ORIGIN_GRID_ID' = 'grid_id')) %>%
rename(ORIGIN_TRAIN_EXIT_CT=train_exit_ct,
ORIGIN_PRESCHOOL_CT=preschool_ct,
ORIGIN_BUSINESS_CT=business_ct,
ORIGIN_FINSERV_CT=finserv_ct,
ORIGIN_SCH_CT=sch_ct,
ORIGIN_RENTAL_CT=hdb_rental_ct,
ORIGIN_1ROOM_CT=hdb_1room_ct,
ORIGIN_2ROOM_CT=hdb_2room_ct,
ORIGIN_3ROOM_CT=hdb_3room_ct,
ORIGIN_4ROOM_CT=hdb_4room_ct,
ORIGIN_5ROOM_CT=hdb_5room_ct,
ORIGIN_EXEC_CT=hdb_exec_ct,
ORIGIN_MULTI_CT=hdb_multi_ct,
ORIGIN_STUDIO_CT=hdb_studio_ct,
ORIGIN_OWNER_CT=hdb_owner_ct) %>%
select(-c(num_bs,geometry))flow_data1 <- flow_data1 %>%
left_join(bs_count,
by = c('DESTIN_GRID_ID' = 'grid_id')) %>%
rename(DESTIN_TRAIN_EXIT_CT=train_exit_ct,
DESTIN_PRESCHOOL_CT=preschool_ct,
DESTIN_BUSINESS_CT=business_ct,
DESTIN_FINSERV_CT=finserv_ct,
DESTIN_SCH_CT=sch_ct,
DESTIN_RENTAL_CT=hdb_rental_ct,
DESTIN_1ROOM_CT=hdb_1room_ct,
DESTIN_2ROOM_CT=hdb_2room_ct,
DESTIN_3ROOM_CT=hdb_3room_ct,
DESTIN_4ROOM_CT=hdb_4room_ct,
DESTIN_5ROOM_CT=hdb_5room_ct,
DESTIN_EXEC_CT=hdb_exec_ct,
DESTIN_MULTI_CT=hdb_multi_ct,
DESTIN_STUDIO_CT=hdb_studio_ct,
DESTIN_OWNER_CT=hdb_owner_ct) %>%
select(-c(num_bs, geometry))Write flow_data1 into local disk.
Read the flow_data1 back into R
Calibrating Spatial Interaction Models
Basic data exploration of flow_data1 df.
‘TRIPS’ are all positive values, its distribution is highly skewed to the right.
These two variables are not linearly related, suggesting that we could apply data transformation on them.
The first choice of our regression model is the Poisson Regression in glm() function.
Why Poisson regression?
our target variable (TRIPS) is count-based
target variable can only be positive values (unlike Linear regression where positive and negative values are possible; negative TRIPS do not make sense)
a type of generalised linear model (GLM) used to count data
residuals may follow a asymmetric distribution around the mean (meaning outcomes on either sides of the mean are NOT equally likely.)
It means that the probability of commuting is not described by a continuous (normal) probability distribution, but a discrete probability distribution such as the Poisson distribution
It would also mean that we do not have to adhere to the assumptions of the Linear Regression Model:
dependent variable and predictors have linear relationship
residual errors (predicted - actual) are normally distributed, have a constant variance and unrelated with one another.
Check independent variables for zero values
Since we have chosen the Poisson regression, which is based on log and log 0 is undefined, it is important for us to ensure that are no 0 values in the explanatory variables.
In the code chunk below, summary() of Base R is used to compute the summary statistics of all variables in flow_data1 data frame.
ORIGIN_GRID_ID DESTIN_GRID_ID TRIPS FlowNoIntra
1960 : 290 1474 : 344 Min. : 1.0 Min. : 1.0
1477 : 288 1452 : 331 1st Qu.: 7.0 1st Qu.: 7.0
1474 : 278 1516 : 314 Median : 34.0 Median : 34.0
1496 : 272 1960 : 289 Mean : 329.4 Mean : 329.4
1623 : 267 1477 : 288 3rd Qu.: 158.0 3rd Qu.: 158.0
1480 : 266 1494 : 283 Max. :75374.0 Max. :75374.0
(Other):60525 (Other):60337
offset dist ORIGIN_TRAIN_EXIT_CT ORIGIN_PRESCHOOL_CT
Min. :1 Min. : 750 Min. : 0.000 Min. : 0.000
1st Qu.:1 1st Qu.: 2704 1st Qu.: 0.000 1st Qu.: 1.000
Median :1 Median : 5250 Median : 0.000 Median : 3.000
Mean :1 Mean : 6236 Mean : 1.234 Mean : 3.363
3rd Qu.:1 3rd Qu.: 8649 3rd Qu.: 2.000 3rd Qu.: 5.000
Max. :1 Max. :24784 Max. :13.000 Max. :18.000
ORIGIN_BUSINESS_CT ORIGIN_FINSERV_CT ORIGIN_SCH_CT ORIGIN_RENTAL_CT
Min. : 0.000 Min. : 0.000 Min. :0.0000 Min. : 0.00
1st Qu.: 0.000 1st Qu.: 1.000 1st Qu.:0.0000 1st Qu.: 0.00
Median : 1.000 Median : 3.000 Median :0.0000 Median : 0.00
Mean : 6.363 Mean : 7.149 Mean :0.5761 Mean : 197.38
3rd Qu.: 6.000 3rd Qu.: 8.000 3rd Qu.:1.0000 3rd Qu.: 23.25
Max. :97.000 Max. :130.000 Max. :4.0000 Max. :2893.00
ORIGIN_1ROOM_CT ORIGIN_2ROOM_CT ORIGIN_3ROOM_CT ORIGIN_4ROOM_CT
Min. : 0.0000 Min. : 0.00 Min. : 0 Min. : 0
1st Qu.: 0.0000 1st Qu.: 0.00 1st Qu.: 0 1st Qu.: 0
Median : 0.0000 Median : 0.00 Median : 1030 Median : 6048
Mean : 0.3568 Mean : 78.21 Mean : 4880 Mean :15149
3rd Qu.: 0.0000 3rd Qu.: 44.00 3rd Qu.: 6700 3rd Qu.:25683
Max. :255.0000 Max. :4164.00 Max. :40960 Max. :99162
ORIGIN_5ROOM_CT ORIGIN_EXEC_CT ORIGIN_MULTI_CT ORIGIN_STUDIO_CT
Min. : 0 Min. : 0.0 Min. : 0.000 Min. : 0.00
1st Qu.: 0 1st Qu.: 0.0 1st Qu.: 0.000 1st Qu.: 0.00
Median : 2119 Median : 0.0 Median : 0.000 Median : 0.00
Mean : 5135 Mean : 424.6 Mean : 6.987 Mean : 14.57
3rd Qu.: 7605 3rd Qu.: 448.0 3rd Qu.: 0.000 3rd Qu.: 0.00
Max. :61945 Max. :6776.0 Max. :1976.000 Max. :252.00
ORIGIN_OWNER_CT DESTIN_TRAIN_EXIT_CT DESTIN_PRESCHOOL_CT DESTIN_BUSINESS_CT
Min. : 0 Min. : 0.000 Min. : 0.000 Min. : 0.000
1st Qu.: 0 1st Qu.: 0.000 1st Qu.: 1.000 1st Qu.: 0.000
Median : 12883 Median : 0.000 Median : 3.000 Median : 1.000
Mean : 25689 Mean : 1.348 Mean : 3.208 Mean : 7.362
3rd Qu.: 46830 3rd Qu.: 2.000 3rd Qu.: 5.000 3rd Qu.: 6.000
Max. :130585 Max. :13.000 Max. :18.000 Max. :97.000
DESTIN_FINSERV_CT DESTIN_SCH_CT DESTIN_RENTAL_CT DESTIN_1ROOM_CT
Min. : 0.000 Min. :0.000 Min. : 0.0 Min. : 0.0000
1st Qu.: 1.000 1st Qu.:0.000 1st Qu.: 0.0 1st Qu.: 0.0000
Median : 3.000 Median :0.000 Median : 0.0 Median : 0.0000
Mean : 7.929 Mean :0.538 Mean : 188.8 Mean : 0.3937
3rd Qu.: 9.000 3rd Qu.:1.000 3rd Qu.: 15.0 3rd Qu.: 0.0000
Max. :130.000 Max. :4.000 Max. :2893.0 Max. :255.0000
DESTIN_2ROOM_CT DESTIN_3ROOM_CT DESTIN_4ROOM_CT DESTIN_5ROOM_CT
Min. : 0.00 Min. : 0 Min. : 0 Min. : 0
1st Qu.: 0.00 1st Qu.: 0 1st Qu.: 0 1st Qu.: 0
Median : 0.00 Median : 660 Median : 4788 Median : 1092
Mean : 71.86 Mean : 4556 Mean :13828 Mean : 4634
3rd Qu.: 16.00 3rd Qu.: 6170 3rd Qu.:24171 3rd Qu.: 6877
Max. :4164.00 Max. :40960 Max. :99162 Max. :61945
DESTIN_EXEC_CT DESTIN_MULTI_CT DESTIN_STUDIO_CT DESTIN_OWNER_CT
Min. : 0.0 Min. : 0.000 Min. : 0.00 Min. : 0
1st Qu.: 0.0 1st Qu.: 0.000 1st Qu.: 0.00 1st Qu.: 0
Median : 0.0 Median : 0.000 Median : 0.00 Median : 9446
Mean : 374.5 Mean : 6.812 Mean : 13.23 Mean : 23484
3rd Qu.: 288.0 3rd Qu.: 0.000 3rd Qu.: 0.00 3rd Qu.: 42903
Max. :6776.0 Max. :1976.000 Max. :252.00 Max. :130585
The print report above reveals that variables all consist of 0 values.
In view of this, code chunk below will be used to use a loop to replace zero values to 0.99 (randomly chosen value that is close to 0). The names of the fields to be transformed will be stored in ‘columns_to_transform’ variable.
columns_to_transform <- c(
"ORIGIN_TRAIN_EXIT_CT", "ORIGIN_PRESCHOOL_CT", "ORIGIN_BUSINESS_CT", "ORIGIN_FINSERV_CT", "ORIGIN_SCH_CT", "ORIGIN_RENTAL_CT", "ORIGIN_1ROOM_CT", "ORIGIN_2ROOM_CT", "ORIGIN_3ROOM_CT", "ORIGIN_4ROOM_CT", "ORIGIN_5ROOM_CT", "ORIGIN_EXEC_CT", "ORIGIN_MULTI_CT", "ORIGIN_STUDIO_CT", "ORIGIN_OWNER_CT", "DESTIN_TRAIN_EXIT_CT", "DESTIN_PRESCHOOL_CT", "DESTIN_BUSINESS_CT", "DESTIN_FINSERV_CT", "DESTIN_SCH_CT", "DESTIN_RENTAL_CT", "DESTIN_1ROOM_CT", "DESTIN_2ROOM_CT", "DESTIN_3ROOM_CT",
"DESTIN_4ROOM_CT", "DESTIN_5ROOM_CT", "DESTIN_EXEC_CT", "DESTIN_MULTI_CT", "DESTIN_STUDIO_CT", "DESTIN_OWNER_CT"
)
for (col in columns_to_transform) {
flow_data1[[col]] <- ifelse(flow_data1[[col]] == 0, 0.99, flow_data1[[col]])
}The four SIMs
For modelling the weekday morning peak passenger flow , we have the following attractive and propulsive variables:
Propulsive: ‘ORIGIN_RENTAL_CT’, ‘ORIGIN_nROOM_CT’, ‘ORIGIN_OWNER_CT’
Attractive: ‘DESTIN_TRAIN_EXIT_CT’, ‘DESTIN_PRESCHOOL_CT’, ‘DESTIN_BUSINESS_CT’, ‘DESTIN_FINSERV_CT’, ‘DESTIN_SCH_CT’
Before we proceed with regression methods, lets us check for multi-collinearity for all our continuous variables.
cor_matrix <- cor(flow_data1[, c("TRIPS","ORIGIN_TRAIN_EXIT_CT", "ORIGIN_PRESCHOOL_CT","ORIGIN_BUSINESS_CT","ORIGIN_FINSERV_CT","ORIGIN_SCH_CT","ORIGIN_RENTAL_CT","ORIGIN_1ROOM_CT","ORIGIN_2ROOM_CT","ORIGIN_3ROOM_CT","ORIGIN_4ROOM_CT","ORIGIN_5ROOM_CT","ORIGIN_EXEC_CT","ORIGIN_MULTI_CT","ORIGIN_STUDIO_CT","ORIGIN_OWNER_CT", "DESTIN_TRAIN_EXIT_CT","DESTIN_PRESCHOOL_CT","DESTIN_BUSINESS_CT","DESTIN_FINSERV_CT","DESTIN_SCH_CT","DESTIN_RENTAL_CT","DESTIN_1ROOM_CT","DESTIN_2ROOM_CT","DESTIN_3ROOM_CT","DESTIN_4ROOM_CT","DESTIN_5ROOM_CT","DESTIN_EXEC_CT","DESTIN_MULTI_CT","DESTIN_STUDIO_CT","DESTIN_OWNER_CT")])
# creating correlation matrix
cor_matrix <- round(cor_matrix,2)
# reduce the size of correlation matrix
melted_corr_matrix <- melt(cor_matrix)
head(melted_corr_matrix) Var1 Var2 value
1 TRIPS TRIPS 1.00
2 ORIGIN_TRAIN_EXIT_CT TRIPS 0.01
3 ORIGIN_PRESCHOOL_CT TRIPS 0.09
4 ORIGIN_BUSINESS_CT TRIPS -0.04
5 ORIGIN_FINSERV_CT TRIPS 0.00
6 ORIGIN_SCH_CT TRIPS 0.04# plotting the correlation heatmap
ggplot(data = melted_corr_matrix, aes(x=Var1, y=Var2,
fill=value)) +
geom_tile() +
geom_text(aes(Var2, Var1, label = value),
color = "black", size = 2.5) +
theme(axis.text.x = element_text(angle = 90, hjust = 1))
The correlation heatmap shows that the origin and destination variable ‘OWNER_CT’ is highly corrrelated with ‘4ROOM_CT’ and ‘5ROOM_CT’. For the subsequent regression methods, we will input either ‘OWNER_CT’ or ‘4ROOM_CT’ and ‘5ROOM_CT’ variables and use the variabels that give us the better result.
The final variables selected here are based on a series of trials and errors; they are statistically significant and would produce the best R-squared results. It turned out that using ‘ORIGIN_4ROOM_CT’ and ‘ORIGIN_5ROOM_CT’ produce better results than ‘ORIGIN_OWNER_CT’.
uncSIM <- glm(formula = TRIPS ~
#log(ORIGIN_TRAIN_EXIT_CT) +
#log(ORIGIN_PRESCHOOL_CT) +
#log(ORIGIN_BUSINESS_CT) +
#log(ORIGIN_FINSERV_CT) +
#log(ORIGIN_SCH_CT) +
log(ORIGIN_RENTAL_CT) +
#log(ORIGIN_1ROOM_CT) +
log(ORIGIN_2ROOM_CT) +
log(ORIGIN_3ROOM_CT) +
log(ORIGIN_4ROOM_CT) +
log(ORIGIN_5ROOM_CT) +
log(ORIGIN_EXEC_CT) +
#log(ORIGIN_MULTI_CT) +
log(ORIGIN_STUDIO_CT) +
#log(ORIGIN_OWNER_CT) +
log(DESTIN_TRAIN_EXIT_CT) +
log(DESTIN_PRESCHOOL_CT) +
log(DESTIN_BUSINESS_CT) +
log(DESTIN_FINSERV_CT) +
log(DESTIN_SCH_CT) +
#log(DESTIN_RENTAL_CT) +
#log(DESTIN_1ROOM_CT) +
#log(DESTIN_2ROOM_CT) +
#log(DESTIN_3ROOM_CT) +
#log(DESTIN_4ROOM_CT) +
#log(DESTIN_5ROOM_CT) +
#log(DESTIN_EXEC_CT) +
#log(DESTIN_MULTI_CT) +
#log(DESTIN_STUDIO_CT) +
#log(DESTIN_OWNER_CT) +
log(dist),
family = poisson(link = "log"),
data = flow_data1,
na.action = na.exclude)The final variables selected here are based on a series of trials and errors; they are statistically significant and would produce the best R-squared results.
orcSIM <- glm(formula= TRIPS ~
ORIGIN_GRID_ID +
log(DESTIN_TRAIN_EXIT_CT) +
log(DESTIN_PRESCHOOL_CT) +
log(DESTIN_BUSINESS_CT) +
log(DESTIN_FINSERV_CT) +
log(DESTIN_SCH_CT) +
#log(DESTIN_RENTAL_CT) +
#log(DESTIN_1ROOM_CT) +
#log(DESTIN_2ROOM_CT) +
#log(DESTIN_3ROOM_CT) +
#log(DESTIN_4ROOM_CT) +
#log(DESTIN_5ROOM_CT) +
#log(DESTIN_EXEC_CT) +
#log(DESTIN_MULTI_CT) +
#log(DESTIN_STUDIO_CT) +
#log(DESTIN_OWNER_CT) +
log(dist)-1,
family = poisson(link='log'),
data = flow_data1,
na.action = na.exclude)decSIM <- glm(formula= TRIPS ~
DESTIN_GRID_ID +
#log(ORIGIN_TRAIN_EXIT_CT) +
#log(ORIGIN_PRESCHOOL_CT) +
#log(ORIGIN_BUSINESS_CT) +
#log(ORIGIN_FINSERV_CT) +
#log(ORIGIN_SCH_CT) +
log(ORIGIN_RENTAL_CT) +
#log(ORIGIN_1ROOM_CT) +
log(ORIGIN_2ROOM_CT) +
log(ORIGIN_3ROOM_CT) +
log(ORIGIN_4ROOM_CT) +
log(ORIGIN_5ROOM_CT) +
log(ORIGIN_EXEC_CT) +
#log(ORIGIN_MULTI_CT) +
log(ORIGIN_STUDIO_CT) +
#log(ORIGIN_OWNER_CT) +
log(dist)-1,
family = poisson(link='log'),
data = flow_data1,
na.action = na.exclude)We will save the output of the four SIMs into rds.
Now reload them into R
Results of SIMs
Unconstrained SIM output
The R-squared value of 0.25 tells us that the explanatory variables are able to explain 25% of the variance in the TRIPS target variable.
CalcRSquared <- function(observed,estimated){
r <- cor(observed,estimated)
R2 <- r^2
R2
}
CalcRSquared(uncSIM$data$TRIPS, uncSIM$fitted.values)[1] 0.2451433Adjusted R-squared. As we increase the number of predictors, the R-square value naturally increases. Thus let us compare the adjusted R-square values instead. To do so, we write custom function:
All the coefficients are statistically significant (refer to next tab). The most influential explanatory variables are distance, destination train exit count and destination school count with coefficients of -1.42, 0.44 and 0.28 respectively. This result is not surprising given the passengers would take bus to MRT stations or schools between 6am-9am on weekdays.
(Intercept) log(ORIGIN_RENTAL_CT) log(ORIGIN_2ROOM_CT)
15.5971526568 -0.0002407122 0.0102928418
log(ORIGIN_3ROOM_CT) log(ORIGIN_4ROOM_CT) log(ORIGIN_5ROOM_CT)
0.0032658938 0.0269209359 0.0911093596
log(ORIGIN_EXEC_CT) log(ORIGIN_STUDIO_CT) log(DESTIN_TRAIN_EXIT_CT)
0.0688556216 0.0109136906 0.4419022283
log(DESTIN_PRESCHOOL_CT) log(DESTIN_BUSINESS_CT) log(DESTIN_FINSERV_CT)
0.0583179446 0.0214182768 0.1490751705
log(DESTIN_SCH_CT) log(dist)
0.2770801526 -1.4224527376 [1] 13
Call:
glm(formula = TRIPS ~ log(ORIGIN_RENTAL_CT) + log(ORIGIN_2ROOM_CT) +
log(ORIGIN_3ROOM_CT) + log(ORIGIN_4ROOM_CT) + log(ORIGIN_5ROOM_CT) +
log(ORIGIN_EXEC_CT) + log(ORIGIN_STUDIO_CT) + log(DESTIN_TRAIN_EXIT_CT) +
log(DESTIN_PRESCHOOL_CT) + log(DESTIN_BUSINESS_CT) + log(DESTIN_FINSERV_CT) +
log(DESTIN_SCH_CT) + log(dist), family = poisson(link = "log"),
data = flow_data1, na.action = na.exclude)
Deviance Residuals:
Min 1Q Median 3Q Max
-142.80 -13.77 -7.16 -0.95 854.68
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 1.560e+01 2.163e-03 7211.430 < 2e-16 ***
log(ORIGIN_RENTAL_CT) -2.407e-04 9.113e-05 -2.641 0.00826 **
log(ORIGIN_2ROOM_CT) 1.029e-02 1.145e-04 89.859 < 2e-16 ***
log(ORIGIN_3ROOM_CT) 3.266e-03 8.843e-05 36.931 < 2e-16 ***
log(ORIGIN_4ROOM_CT) 2.692e-02 1.786e-04 150.714 < 2e-16 ***
log(ORIGIN_5ROOM_CT) 9.111e-02 1.834e-04 496.746 < 2e-16 ***
log(ORIGIN_EXEC_CT) 6.886e-02 9.171e-05 750.762 < 2e-16 ***
log(ORIGIN_STUDIO_CT) 1.091e-02 1.404e-04 77.746 < 2e-16 ***
log(DESTIN_TRAIN_EXIT_CT) 4.419e-01 4.118e-04 1073.180 < 2e-16 ***
log(DESTIN_PRESCHOOL_CT) 5.832e-02 3.332e-04 175.046 < 2e-16 ***
log(DESTIN_BUSINESS_CT) 2.142e-02 1.890e-04 113.320 < 2e-16 ***
log(DESTIN_FINSERV_CT) 1.491e-01 2.743e-04 543.545 < 2e-16 ***
log(DESTIN_SCH_CT) 2.771e-01 7.125e-04 388.869 < 2e-16 ***
log(dist) -1.422e+00 2.742e-04 -5187.662 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 82068169 on 62185 degrees of freedom
Residual deviance: 41784217 on 62172 degrees of freedom
AIC: 42120350
Number of Fisher Scoring iterations: 7Origin Constrained SIM output
The R-squared value of 0.38 tells us that the explanatory variables are able to explain 38 % of the variance in the TRIPS target variable. It has higher R-squared value than the unconstrained model because it has additional ‘knowledge’ of the origin population data.
Adjusted R-squared
All the coefficients are statistically significant (refer to next tab). The most influential explanatory variables are distance, destination train exit count and destination school count with coefficients of -1.50, 0.49 and 0.28 respectively. This result is consistent with unconstrained model.
Call:
glm(formula = TRIPS ~ ORIGIN_GRID_ID + log(DESTIN_TRAIN_EXIT_CT) +
log(DESTIN_PRESCHOOL_CT) + log(DESTIN_BUSINESS_CT) + log(DESTIN_FINSERV_CT) +
log(DESTIN_SCH_CT) + log(dist) - 1, family = poisson(link = "log"),
data = flow_data1, na.action = na.exclude)
Deviance Residuals:
Min 1Q Median 3Q Max
-267.73 -11.17 -4.59 1.45 426.36
Coefficients:
Estimate Std. Error z value Pr(>|z|)
ORIGIN_GRID_ID23 14.2200929 0.1280575 111.045 <2e-16 ***
ORIGIN_GRID_ID44 14.8773494 0.1525177 97.545 <2e-16 ***
ORIGIN_GRID_ID46 13.8195046 0.0971516 142.247 <2e-16 ***
ORIGIN_GRID_ID66 14.5589073 0.1348607 107.955 <2e-16 ***
ORIGIN_GRID_ID67 15.5853691 0.0270728 575.683 <2e-16 ***
ORIGIN_GRID_ID68 13.2469013 0.1147265 115.465 <2e-16 ***
ORIGIN_GRID_ID86 14.0994155 0.0860895 163.776 <2e-16 ***
ORIGIN_GRID_ID87 15.8502187 0.0769627 205.947 <2e-16 ***
ORIGIN_GRID_ID88 16.0143576 0.0202258 791.778 <2e-16 ***
ORIGIN_GRID_ID89 14.1173112 0.0503566 280.347 <2e-16 ***
ORIGIN_GRID_ID90 13.2364895 0.1302053 101.659 <2e-16 ***
ORIGIN_GRID_ID109 13.8645082 0.1066206 130.036 <2e-16 ***
ORIGIN_GRID_ID110 14.1227741 0.0808722 174.631 <2e-16 ***
ORIGIN_GRID_ID111 17.0031251 0.0120958 1405.706 <2e-16 ***
ORIGIN_GRID_ID112 13.4152509 0.0718260 186.774 <2e-16 ***
ORIGIN_GRID_ID128 16.4724259 0.0255197 645.479 <2e-16 ***
ORIGIN_GRID_ID129 13.6573101 0.1889958 72.262 <2e-16 ***
ORIGIN_GRID_ID130 14.5479993 0.0558517 260.476 <2e-16 ***
ORIGIN_GRID_ID131 15.3061603 0.0324626 471.501 <2e-16 ***
ORIGIN_GRID_ID132 13.9311450 0.0567438 245.510 <2e-16 ***
ORIGIN_GRID_ID133 13.9162833 0.0427279 325.696 <2e-16 ***
ORIGIN_GRID_ID134 16.1832650 0.0262282 617.018 <2e-16 ***
ORIGIN_GRID_ID150 16.7080841 0.0213182 783.746 <2e-16 ***
ORIGIN_GRID_ID151 13.5106960 0.0822248 164.314 <2e-16 ***
ORIGIN_GRID_ID152 13.3287412 0.0870623 153.094 <2e-16 ***
ORIGIN_GRID_ID153 14.4828399 0.0451304 320.911 <2e-16 ***
ORIGIN_GRID_ID154 17.0483986 0.0096079 1774.407 <2e-16 ***
ORIGIN_GRID_ID155 13.8803955 0.0396137 350.394 <2e-16 ***
ORIGIN_GRID_ID156 14.5514586 0.0549187 264.964 <2e-16 ***
ORIGIN_GRID_ID172 15.3888515 0.0668511 230.196 <2e-16 ***
ORIGIN_GRID_ID174 14.3578879 0.0481527 298.174 <2e-16 ***
ORIGIN_GRID_ID175 16.5491451 0.0106605 1552.385 <2e-16 ***
ORIGIN_GRID_ID176 17.6227860 0.0066199 2662.104 <2e-16 ***
ORIGIN_GRID_ID195 13.2614994 0.0877276 151.167 <2e-16 ***
ORIGIN_GRID_ID196 13.8758674 0.0429638 322.967 <2e-16 ***
ORIGIN_GRID_ID197 12.9278073 0.1336460 96.732 <2e-16 ***
ORIGIN_GRID_ID215 14.0445439 0.0985568 142.502 <2e-16 ***
ORIGIN_GRID_ID216 17.9910067 0.0055659 3232.377 <2e-16 ***
ORIGIN_GRID_ID217 15.2411143 0.0222760 684.195 <2e-16 ***
ORIGIN_GRID_ID237 13.5777312 0.3015201 45.031 <2e-16 ***
ORIGIN_GRID_ID238 13.5977695 0.0762790 178.264 <2e-16 ***
ORIGIN_GRID_ID239 13.8507904 0.1443544 95.950 <2e-16 ***
ORIGIN_GRID_ID257 14.1427612 0.0622922 227.039 <2e-16 ***
ORIGIN_GRID_ID258 14.8757766 0.0289278 514.237 <2e-16 ***
ORIGIN_GRID_ID259 14.6145943 0.0413278 353.626 <2e-16 ***
ORIGIN_GRID_ID278 15.6270388 0.0374807 416.936 <2e-16 ***
ORIGIN_GRID_ID279 13.5772451 0.0487796 278.338 <2e-16 ***
ORIGIN_GRID_ID280 13.9648940 0.0506163 275.897 <2e-16 ***
ORIGIN_GRID_ID298 11.2559939 0.3779699 29.780 <2e-16 ***
ORIGIN_GRID_ID299 13.6742969 0.0597962 228.682 <2e-16 ***
ORIGIN_GRID_ID300 17.0436194 0.0088221 1931.916 <2e-16 ***
ORIGIN_GRID_ID320 14.2457612 0.0520255 273.823 <2e-16 ***
ORIGIN_GRID_ID321 14.1320377 0.0803482 175.885 <2e-16 ***
ORIGIN_GRID_ID322 15.5380661 0.0411558 377.543 <2e-16 ***
ORIGIN_GRID_ID340 15.6604330 0.0311676 502.459 <2e-16 ***
ORIGIN_GRID_ID341 13.9592617 0.0504848 276.505 <2e-16 ***
ORIGIN_GRID_ID342 14.7106236 0.0428844 343.029 <2e-16 ***
ORIGIN_GRID_ID363 15.4069086 0.0400184 384.996 <2e-16 ***
ORIGIN_GRID_ID364 15.1980479 0.0275898 550.858 <2e-16 ***
ORIGIN_GRID_ID383 14.7932580 0.0338891 436.520 <2e-16 ***
ORIGIN_GRID_ID384 13.7568230 0.0526699 261.189 <2e-16 ***
ORIGIN_GRID_ID385 13.9395186 0.0700395 199.024 <2e-16 ***
ORIGIN_GRID_ID404 15.6771951 0.0306499 511.492 <2e-16 ***
ORIGIN_GRID_ID405 14.6724077 0.0562908 260.654 <2e-16 ***
ORIGIN_GRID_ID406 18.9453028 0.0032361 5854.453 <2e-16 ***
ORIGIN_GRID_ID407 14.7633362 0.0497344 296.844 <2e-16 ***
ORIGIN_GRID_ID408 15.5179225 0.0254752 609.138 <2e-16 ***
ORIGIN_GRID_ID425 13.0327961 0.1037141 125.661 <2e-16 ***
ORIGIN_GRID_ID426 14.9241514 0.0311930 478.446 <2e-16 ***
ORIGIN_GRID_ID427 13.5595934 0.0487227 278.301 <2e-16 ***
ORIGIN_GRID_ID428 13.0855450 0.1250187 104.669 <2e-16 ***
ORIGIN_GRID_ID429 16.0024308 0.0216231 740.061 <2e-16 ***
ORIGIN_GRID_ID446 14.2394718 0.0712786 199.772 <2e-16 ***
ORIGIN_GRID_ID447 14.1804770 0.0412549 343.728 <2e-16 ***
ORIGIN_GRID_ID448 14.9741053 0.0282026 530.948 <2e-16 ***
ORIGIN_GRID_ID449 17.7250244 0.0066885 2650.061 <2e-16 ***
ORIGIN_GRID_ID450 15.5961877 0.0207532 751.508 <2e-16 ***
ORIGIN_GRID_ID468 14.8986417 0.0330686 450.537 <2e-16 ***
ORIGIN_GRID_ID469 15.8704980 0.0157297 1008.951 <2e-16 ***
ORIGIN_GRID_ID470 18.0547639 0.0050231 3594.331 <2e-16 ***
ORIGIN_GRID_ID471 16.3434880 0.0176816 924.321 <2e-16 ***
ORIGIN_GRID_ID488 14.6068207 0.0593768 246.002 <2e-16 ***
ORIGIN_GRID_ID489 12.0495030 0.1690426 71.281 <2e-16 ***
ORIGIN_GRID_ID490 16.4550099 0.0127186 1293.774 <2e-16 ***
ORIGIN_GRID_ID491 16.9393951 0.0081602 2075.861 <2e-16 ***
ORIGIN_GRID_ID493 11.6305166 0.2182278 53.295 <2e-16 ***
ORIGIN_GRID_ID494 13.6055257 0.0795836 170.959 <2e-16 ***
ORIGIN_GRID_ID509 14.7735127 0.0389776 379.025 <2e-16 ***
ORIGIN_GRID_ID510 15.4066411 0.0270173 570.250 <2e-16 ***
ORIGIN_GRID_ID511 16.0319567 0.0116712 1373.636 <2e-16 ***
ORIGIN_GRID_ID512 18.5628927 0.0037248 4983.578 <2e-16 ***
ORIGIN_GRID_ID513 15.2871367 0.0277200 551.483 <2e-16 ***
ORIGIN_GRID_ID514 14.0067288 0.0557666 251.167 <2e-16 ***
ORIGIN_GRID_ID515 12.1411840 0.2236166 54.295 <2e-16 ***
ORIGIN_GRID_ID530 13.9167015 0.0905591 153.675 <2e-16 ***
ORIGIN_GRID_ID531 15.2715067 0.0205980 741.408 <2e-16 ***
ORIGIN_GRID_ID532 14.5582892 0.0272157 534.923 <2e-16 ***
ORIGIN_GRID_ID533 18.3388615 0.0037941 4833.476 <2e-16 ***
ORIGIN_GRID_ID534 18.7249699 0.0040739 4596.362 <2e-16 ***
ORIGIN_GRID_ID536 15.4078079 0.0272822 564.757 <2e-16 ***
ORIGIN_GRID_ID537 12.4233495 0.1924615 64.550 <2e-16 ***
ORIGIN_GRID_ID538 12.7581088 0.2582099 49.410 <2e-16 ***
ORIGIN_GRID_ID539 12.3530196 1.0000028 12.353 <2e-16 ***
ORIGIN_GRID_ID551 14.2804526 0.0570143 250.472 <2e-16 ***
ORIGIN_GRID_ID552 15.7590517 0.0376911 418.110 <2e-16 ***
ORIGIN_GRID_ID553 14.9998110 0.0188981 793.722 <2e-16 ***
ORIGIN_GRID_ID554 18.2952346 0.0040177 4553.603 <2e-16 ***
ORIGIN_GRID_ID555 17.5956662 0.0078365 2245.336 <2e-16 ***
ORIGIN_GRID_ID559 13.5559528 0.1066215 127.141 <2e-16 ***
ORIGIN_GRID_ID560 15.4753491 0.0568479 272.224 <2e-16 ***
ORIGIN_GRID_ID561 9.8841888 1.0000018 9.884 <2e-16 ***
ORIGIN_GRID_ID572 10.6270576 0.5773538 18.406 <2e-16 ***
ORIGIN_GRID_ID573 14.0502881 0.0477143 294.467 <2e-16 ***
ORIGIN_GRID_ID574 15.0001241 0.0383192 391.452 <2e-16 ***
ORIGIN_GRID_ID575 19.1682395 0.0028298 6773.686 <2e-16 ***
ORIGIN_GRID_ID576 17.7956535 0.0053465 3328.472 <2e-16 ***
ORIGIN_GRID_ID578 13.0787629 0.1042784 125.422 <2e-16 ***
ORIGIN_GRID_ID582 13.3431065 0.1097835 121.540 <2e-16 ***
ORIGIN_GRID_ID583 13.1309410 0.5773558 22.743 <2e-16 ***
ORIGIN_GRID_ID584 16.2945654 0.0586791 277.689 <2e-16 ***
ORIGIN_GRID_ID593 14.3197691 0.0523860 273.351 <2e-16 ***
ORIGIN_GRID_ID594 15.2977149 0.0265934 575.244 <2e-16 ***
ORIGIN_GRID_ID595 14.8217754 0.0201391 735.969 <2e-16 ***
ORIGIN_GRID_ID596 17.6225187 0.0047294 3726.153 <2e-16 ***
ORIGIN_GRID_ID597 14.4974331 0.0613516 236.301 <2e-16 ***
ORIGIN_GRID_ID603 13.4745111 0.1178703 114.316 <2e-16 ***
ORIGIN_GRID_ID604 13.9557787 0.1924670 72.510 <2e-16 ***
ORIGIN_GRID_ID615 13.5290716 0.0508748 265.929 <2e-16 ***
ORIGIN_GRID_ID616 14.5123790 0.0330688 438.853 <2e-16 ***
ORIGIN_GRID_ID617 15.3246252 0.0194368 788.432 <2e-16 ***
ORIGIN_GRID_ID618 18.1810105 0.0041814 4348.072 <2e-16 ***
ORIGIN_GRID_ID620 15.3127541 0.0323398 473.495 <2e-16 ***
ORIGIN_GRID_ID637 13.9390564 0.0455937 305.723 <2e-16 ***
ORIGIN_GRID_ID638 17.7304485 0.0045768 3874.022 <2e-16 ***
ORIGIN_GRID_ID657 15.6536101 0.0174830 895.361 <2e-16 ***
ORIGIN_GRID_ID658 16.9925627 0.0067897 2502.682 <2e-16 ***
ORIGIN_GRID_ID659 17.3224322 0.0058154 2978.736 <2e-16 ***
ORIGIN_GRID_ID660 18.2429896 0.0038417 4748.685 <2e-16 ***
ORIGIN_GRID_ID662 18.0266875 0.0072690 2479.943 <2e-16 ***
ORIGIN_GRID_ID677 15.6872554 0.0238963 656.472 <2e-16 ***
ORIGIN_GRID_ID678 13.5115872 0.0501068 269.656 <2e-16 ***
ORIGIN_GRID_ID679 18.1611849 0.0040289 4507.692 <2e-16 ***
ORIGIN_GRID_ID680 18.2134765 0.0040161 4535.123 <2e-16 ***
ORIGIN_GRID_ID681 17.2826689 0.0089347 1934.329 <2e-16 ***
ORIGIN_GRID_ID699 15.1606969 0.0239099 634.075 <2e-16 ***
ORIGIN_GRID_ID700 17.1782060 0.0065366 2627.986 <2e-16 ***
ORIGIN_GRID_ID701 17.2719093 0.0065787 2625.418 <2e-16 ***
ORIGIN_GRID_ID702 18.0977392 0.0040026 4521.522 <2e-16 ***
ORIGIN_GRID_ID704 14.8603526 0.0344483 431.381 <2e-16 ***
ORIGIN_GRID_ID722 14.9702760 0.0207373 721.901 <2e-16 ***
ORIGIN_GRID_ID725 14.4129948 0.0419766 343.358 <2e-16 ***
ORIGIN_GRID_ID741 15.7723527 0.0169648 929.710 <2e-16 ***
ORIGIN_GRID_ID743 15.5014809 0.0136331 1137.044 <2e-16 ***
ORIGIN_GRID_ID744 17.5008054 0.0051450 3401.511 <2e-16 ***
ORIGIN_GRID_ID761 15.2070425 0.0305326 498.060 <2e-16 ***
ORIGIN_GRID_ID762 17.2137581 0.0075422 2282.323 <2e-16 ***
ORIGIN_GRID_ID763 13.9913444 0.0305299 458.283 <2e-16 ***
ORIGIN_GRID_ID764 17.9692060 0.0039851 4509.048 <2e-16 ***
ORIGIN_GRID_ID765 17.2986000 0.0088438 1956.012 <2e-16 ***
ORIGIN_GRID_ID767 18.6542277 0.0041143 4534.027 <2e-16 ***
ORIGIN_GRID_ID772 13.5066020 0.0816777 165.365 <2e-16 ***
ORIGIN_GRID_ID784 14.0514561 0.0287638 488.512 <2e-16 ***
ORIGIN_GRID_ID785 17.2678330 0.0048106 3589.538 <2e-16 ***
ORIGIN_GRID_ID786 16.8103960 0.0065821 2553.946 <2e-16 ***
ORIGIN_GRID_ID787 17.4209686 0.0077253 2255.067 <2e-16 ***
ORIGIN_GRID_ID788 17.9527975 0.0057412 3127.036 <2e-16 ***
ORIGIN_GRID_ID789 16.5768595 0.0112342 1475.576 <2e-16 ***
ORIGIN_GRID_ID803 13.4317728 0.0647180 207.543 <2e-16 ***
ORIGIN_GRID_ID804 18.1138234 0.0045415 3988.513 <2e-16 ***
ORIGIN_GRID_ID805 17.9544466 0.0038886 4617.233 <2e-16 ***
ORIGIN_GRID_ID806 17.4545038 0.0047929 3641.764 <2e-16 ***
ORIGIN_GRID_ID807 18.3265221 0.0046017 3982.589 <2e-16 ***
ORIGIN_GRID_ID808 16.6402790 0.0116491 1428.461 <2e-16 ***
ORIGIN_GRID_ID809 18.1994619 0.0039140 4649.876 <2e-16 ***
ORIGIN_GRID_ID810 17.5321400 0.0061003 2873.982 <2e-16 ***
ORIGIN_GRID_ID814 15.1570231 0.0278119 544.984 <2e-16 ***
ORIGIN_GRID_ID819 19.6979432 0.0193311 1018.977 <2e-16 ***
ORIGIN_GRID_ID824 14.4409775 0.0421605 342.524 <2e-16 ***
ORIGIN_GRID_ID826 15.6344481 0.0109118 1432.799 <2e-16 ***
ORIGIN_GRID_ID827 17.7083609 0.0043220 4097.294 <2e-16 ***
ORIGIN_GRID_ID828 17.7848747 0.0042032 4231.233 <2e-16 ***
ORIGIN_GRID_ID829 17.8185853 0.0049990 3564.401 <2e-16 ***
ORIGIN_GRID_ID830 17.8986561 0.0054204 3302.121 <2e-16 ***
ORIGIN_GRID_ID831 18.6205263 0.0034085 5463.002 <2e-16 ***
ORIGIN_GRID_ID832 17.7384935 0.0068149 2602.889 <2e-16 ***
ORIGIN_GRID_ID835 15.1484249 0.0297156 509.781 <2e-16 ***
ORIGIN_GRID_ID844 13.5305171 0.0781170 173.208 <2e-16 ***
ORIGIN_GRID_ID846 17.1455242 0.0058470 2932.341 <2e-16 ***
ORIGIN_GRID_ID847 15.9272976 0.0105832 1504.957 <2e-16 ***
ORIGIN_GRID_ID848 17.2632178 0.0053057 3253.737 <2e-16 ***
ORIGIN_GRID_ID849 16.4284891 0.0082654 1987.621 <2e-16 ***
ORIGIN_GRID_ID850 17.1608405 0.0060867 2819.411 <2e-16 ***
ORIGIN_GRID_ID851 17.6746193 0.0045862 3853.840 <2e-16 ***
ORIGIN_GRID_ID852 17.1566318 0.0065653 2613.226 <2e-16 ***
ORIGIN_GRID_ID853 19.0551807 0.0040104 4751.438 <2e-16 ***
ORIGIN_GRID_ID854 15.3822454 0.0263514 583.735 <2e-16 ***
ORIGIN_GRID_ID855 14.1359635 0.0455940 310.040 <2e-16 ***
ORIGIN_GRID_ID856 15.7895069 0.0187116 843.836 <2e-16 ***
ORIGIN_GRID_ID866 15.1474251 0.0286610 528.503 <2e-16 ***
ORIGIN_GRID_ID867 15.9371008 0.0126848 1256.394 <2e-16 ***
ORIGIN_GRID_ID868 14.9376622 0.0220215 678.321 <2e-16 ***
ORIGIN_GRID_ID869 17.8714449 0.0061723 2895.415 <2e-16 ***
ORIGIN_GRID_ID870 18.2740445 0.0034911 5234.423 <2e-16 ***
ORIGIN_GRID_ID871 17.7872740 0.0063121 2817.980 <2e-16 ***
ORIGIN_GRID_ID872 15.8636017 0.0120010 1321.858 <2e-16 ***
ORIGIN_GRID_ID873 16.1296205 0.0109515 1472.825 <2e-16 ***
ORIGIN_GRID_ID874 16.5039349 0.0084781 1946.661 <2e-16 ***
ORIGIN_GRID_ID875 13.4433420 0.0697043 192.863 <2e-16 ***
ORIGIN_GRID_ID876 14.6143346 0.0315324 463.470 <2e-16 ***
ORIGIN_GRID_ID877 13.9076468 0.0429201 324.036 <2e-16 ***
ORIGIN_GRID_ID887 15.6546459 0.0143154 1093.553 <2e-16 ***
ORIGIN_GRID_ID888 16.8082236 0.0077614 2165.626 <2e-16 ***
ORIGIN_GRID_ID889 14.0273451 0.0349634 401.201 <2e-16 ***
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ORIGIN_GRID_ID891 16.6345149 0.0117708 1413.201 <2e-16 ***
ORIGIN_GRID_ID893 17.7054494 0.0044350 3992.217 <2e-16 ***
ORIGIN_GRID_ID894 16.0230709 0.0109691 1460.750 <2e-16 ***
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ORIGIN_GRID_ID992 16.6036021 0.0073918 2246.207 <2e-16 ***
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ORIGIN_GRID_ID998 18.1101908 0.0042654 4245.804 <2e-16 ***
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ORIGIN_GRID_ID1001 15.4676741 0.0256796 602.334 <2e-16 ***
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ORIGIN_GRID_ID1016 16.4992166 0.0082043 2011.047 <2e-16 ***
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ORIGIN_GRID_ID1024 18.0553463 0.0047538 3798.080 <2e-16 ***
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ORIGIN_GRID_ID1066 17.5567013 0.0053851 3260.235 <2e-16 ***
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ORIGIN_GRID_ID1077 15.7828736 0.0113655 1388.660 <2e-16 ***
ORIGIN_GRID_ID1079 17.0907666 0.0060327 2833.004 <2e-16 ***
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ORIGIN_GRID_ID1095 14.0157361 0.0442386 316.821 <2e-16 ***
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ORIGIN_GRID_ID1178 15.4326560 0.0120576 1279.914 <2e-16 ***
ORIGIN_GRID_ID1179 16.0878638 0.0080337 2002.544 <2e-16 ***
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ORIGIN_GRID_ID1257 17.9854862 0.0055250 3255.317 <2e-16 ***
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ORIGIN_GRID_ID1266 16.3761974 0.0083714 1956.219 <2e-16 ***
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ORIGIN_GRID_ID1273 15.9803214 0.0133104 1200.586 <2e-16 ***
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ORIGIN_GRID_ID1278 15.5812797 0.0149164 1044.576 <2e-16 ***
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ORIGIN_GRID_ID1330 16.3441646 0.0091500 1786.244 <2e-16 ***
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ORIGIN_GRID_ID1336 12.9351289 0.1386957 93.263 <2e-16 ***
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ORIGIN_GRID_ID1338 12.0992376 0.1139800 106.152 <2e-16 ***
ORIGIN_GRID_ID1339 17.9952000 0.0042708 4213.511 <2e-16 ***
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ORIGIN_GRID_ID1341 13.6458603 0.2236186 61.023 <2e-16 ***
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ORIGIN_GRID_ID1350 15.8918094 0.0118204 1344.438 <2e-16 ***
ORIGIN_GRID_ID1353 15.6433946 0.0108841 1437.266 <2e-16 ***
ORIGIN_GRID_ID1354 15.3934157 0.0138996 1107.473 <2e-16 ***
ORIGIN_GRID_ID1355 16.2859104 0.0092225 1765.888 <2e-16 ***
ORIGIN_GRID_ID1357 15.3877351 0.0206815 744.034 <2e-16 ***
ORIGIN_GRID_ID1358 16.6824396 0.0079560 2096.832 <2e-16 ***
ORIGIN_GRID_ID1359 17.2205767 0.0057349 3002.793 <2e-16 ***
ORIGIN_GRID_ID1360 17.3891868 0.0057374 3030.868 <2e-16 ***
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ORIGIN_GRID_ID1362 14.7058133 0.0415457 353.967 <2e-16 ***
ORIGIN_GRID_ID1368 15.2543363 0.0097261 1568.398 <2e-16 ***
ORIGIN_GRID_ID1369 14.9731665 0.0105263 1422.451 <2e-16 ***
ORIGIN_GRID_ID1370 16.2418214 0.0059232 2742.081 <2e-16 ***
ORIGIN_GRID_ID1371 15.6375231 0.0112644 1388.220 <2e-16 ***
ORIGIN_GRID_ID1372 15.3358945 0.0140121 1094.471 <2e-16 ***
ORIGIN_GRID_ID1373 13.2959808 0.0526799 252.392 <2e-16 ***
ORIGIN_GRID_ID1374 15.1632552 0.0130053 1165.929 <2e-16 ***
ORIGIN_GRID_ID1375 16.6517057 0.0084499 1970.636 <2e-16 ***
ORIGIN_GRID_ID1376 15.9954156 0.0138788 1152.509 <2e-16 ***
ORIGIN_GRID_ID1379 14.5088421 0.0363143 399.535 <2e-16 ***
ORIGIN_GRID_ID1380 18.2722280 0.0036320 5030.967 <2e-16 ***
ORIGIN_GRID_ID1381 17.9369000 0.0042108 4259.775 <2e-16 ***
ORIGIN_GRID_ID1382 17.5029728 0.0066670 2625.297 <2e-16 ***
ORIGIN_GRID_ID1383 15.0435481 0.0257339 584.582 <2e-16 ***
ORIGIN_GRID_ID1388 15.7440556 0.0076949 2046.039 <2e-16 ***
ORIGIN_GRID_ID1389 14.4203036 0.0128165 1125.132 <2e-16 ***
ORIGIN_GRID_ID1390 15.5149979 0.0079036 1963.032 <2e-16 ***
ORIGIN_GRID_ID1391 15.5800550 0.0086888 1793.120 <2e-16 ***
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ORIGIN_GRID_ID1393 14.6170745 0.0164642 887.808 <2e-16 ***
ORIGIN_GRID_ID1394 15.8902528 0.0084544 1879.515 <2e-16 ***
ORIGIN_GRID_ID1395 15.9483686 0.0083704 1905.333 <2e-16 ***
ORIGIN_GRID_ID1396 17.1110313 0.0055940 3058.802 <2e-16 ***
ORIGIN_GRID_ID1397 17.1751150 0.0057076 3009.181 <2e-16 ***
ORIGIN_GRID_ID1398 16.2253024 0.0118603 1368.035 <2e-16 ***
ORIGIN_GRID_ID1400 17.4748729 0.0067693 2581.487 <2e-16 ***
ORIGIN_GRID_ID1401 18.4073734 0.0033953 5421.480 <2e-16 ***
ORIGIN_GRID_ID1402 17.8354295 0.0047466 3757.542 <2e-16 ***
ORIGIN_GRID_ID1404 17.4058257 0.0157229 1107.037 <2e-16 ***
ORIGIN_GRID_ID1410 15.2052646 0.0088393 1720.185 <2e-16 ***
ORIGIN_GRID_ID1411 15.1204333 0.0091374 1654.780 <2e-16 ***
ORIGIN_GRID_ID1412 15.4893578 0.0074622 2075.718 <2e-16 ***
ORIGIN_GRID_ID1413 16.4896954 0.0058052 2840.517 <2e-16 ***
ORIGIN_GRID_ID1414 16.0241887 0.0071907 2228.473 <2e-16 ***
ORIGIN_GRID_ID1415 15.5672804 0.0102841 1513.726 <2e-16 ***
ORIGIN_GRID_ID1416 16.2551553 0.0076054 2137.311 <2e-16 ***
ORIGIN_GRID_ID1417 16.2542055 0.0072641 2237.616 <2e-16 ***
ORIGIN_GRID_ID1418 17.1548078 0.0053566 3202.556 <2e-16 ***
ORIGIN_GRID_ID1419 16.6725088 0.0072423 2302.090 <2e-16 ***
ORIGIN_GRID_ID1422 17.9167591 0.0049293 3634.740 <2e-16 ***
ORIGIN_GRID_ID1423 18.7526342 0.0036265 5170.981 <2e-16 ***
ORIGIN_GRID_ID1430 15.8516178 0.0069304 2287.259 <2e-16 ***
ORIGIN_GRID_ID1431 15.8131403 0.0059052 2677.829 <2e-16 ***
ORIGIN_GRID_ID1432 15.9586604 0.0056729 2813.129 <2e-16 ***
ORIGIN_GRID_ID1433 14.6928592 0.0182995 802.909 <2e-16 ***
ORIGIN_GRID_ID1434 16.4292280 0.0061201 2684.489 <2e-16 ***
ORIGIN_GRID_ID1435 17.0709124 0.0046343 3683.604 <2e-16 ***
ORIGIN_GRID_ID1436 13.9842673 0.0261317 535.145 <2e-16 ***
ORIGIN_GRID_ID1437 17.2083169 0.0049557 3472.446 <2e-16 ***
ORIGIN_GRID_ID1438 17.6290424 0.0038934 4527.886 <2e-16 ***
ORIGIN_GRID_ID1439 18.2905309 0.0035061 5216.777 <2e-16 ***
ORIGIN_GRID_ID1440 14.7399827 0.0214552 687.012 <2e-16 ***
ORIGIN_GRID_ID1442 17.3707164 0.0068421 2538.799 <2e-16 ***
ORIGIN_GRID_ID1443 18.4203794 0.0039764 4632.440 <2e-16 ***
ORIGIN_GRID_ID1444 17.6105864 0.0079012 2228.862 <2e-16 ***
ORIGIN_GRID_ID1452 14.9312507 0.0093205 1601.981 <2e-16 ***
ORIGIN_GRID_ID1453 15.1686420 0.0089705 1690.951 <2e-16 ***
ORIGIN_GRID_ID1454 14.2314666 0.0210458 676.216 <2e-16 ***
ORIGIN_GRID_ID1455 15.6694949 0.0092809 1688.358 <2e-16 ***
ORIGIN_GRID_ID1456 16.4217049 0.0066669 2463.169 <2e-16 ***
ORIGIN_GRID_ID1457 17.3634639 0.0046096 3766.839 <2e-16 ***
ORIGIN_GRID_ID1458 17.4554630 0.0042133 4142.936 <2e-16 ***
ORIGIN_GRID_ID1459 17.0610094 0.0051390 3319.908 <2e-16 ***
ORIGIN_GRID_ID1460 16.3041597 0.0071663 2275.107 <2e-16 ***
ORIGIN_GRID_ID1461 15.0424704 0.0180273 834.427 <2e-16 ***
ORIGIN_GRID_ID1464 18.7245577 0.0037434 5002.055 <2e-16 ***
ORIGIN_GRID_ID1465 18.3968867 0.0047841 3845.453 <2e-16 ***
ORIGIN_GRID_ID1472 13.4870616 0.0235095 573.685 <2e-16 ***
ORIGIN_GRID_ID1473 14.4834106 0.0118066 1226.727 <2e-16 ***
ORIGIN_GRID_ID1474 15.6586476 0.0063077 2482.451 <2e-16 ***
ORIGIN_GRID_ID1475 16.7596365 0.0049030 3418.254 <2e-16 ***
ORIGIN_GRID_ID1476 16.2864493 0.0070657 2305.002 <2e-16 ***
ORIGIN_GRID_ID1477 17.8661824 0.0033817 5283.137 <2e-16 ***
ORIGIN_GRID_ID1478 16.2805402 0.0070712 2302.383 <2e-16 ***
ORIGIN_GRID_ID1479 16.5284861 0.0063542 2601.207 <2e-16 ***
ORIGIN_GRID_ID1480 18.2621534 0.0032724 5580.583 <2e-16 ***
ORIGIN_GRID_ID1481 15.8698644 0.0107542 1475.691 <2e-16 ***
ORIGIN_GRID_ID1482 15.7358377 0.0141386 1112.968 <2e-16 ***
ORIGIN_GRID_ID1485 18.2289695 0.0049441 3687.038 <2e-16 ***
ORIGIN_GRID_ID1494 14.6700282 0.0142545 1029.147 <2e-16 ***
ORIGIN_GRID_ID1495 14.9560241 0.0091864 1628.054 <2e-16 ***
ORIGIN_GRID_ID1496 16.1333476 0.0053306 3026.529 <2e-16 ***
ORIGIN_GRID_ID1497 16.6815721 0.0056827 2935.495 <2e-16 ***
ORIGIN_GRID_ID1498 17.1848762 0.0045766 3754.932 <2e-16 ***
ORIGIN_GRID_ID1499 17.4939957 0.0041191 4246.995 <2e-16 ***
ORIGIN_GRID_ID1500 17.4370186 0.0057754 3019.193 <2e-16 ***
ORIGIN_GRID_ID1501 17.5535321 0.0041594 4220.165 <2e-16 ***
ORIGIN_GRID_ID1502 17.1896637 0.0051638 3328.871 <2e-16 ***
ORIGIN_GRID_ID1506 13.0285949 0.1078551 120.797 <2e-16 ***
ORIGIN_GRID_ID1515 13.7679080 0.0260755 528.002 <2e-16 ***
ORIGIN_GRID_ID1516 15.3154996 0.0080488 1902.839 <2e-16 ***
ORIGIN_GRID_ID1517 15.8161776 0.0074629 2119.319 <2e-16 ***
ORIGIN_GRID_ID1518 16.1097860 0.0080066 2012.065 <2e-16 ***
ORIGIN_GRID_ID1519 17.6391123 0.0052428 3364.420 <2e-16 ***
ORIGIN_GRID_ID1520 16.2739037 0.0074189 2193.587 <2e-16 ***
ORIGIN_GRID_ID1521 15.6103291 0.0112434 1388.402 <2e-16 ***
ORIGIN_GRID_ID1522 17.8644796 0.0038840 4599.525 <2e-16 ***
ORIGIN_GRID_ID1523 16.1928869 0.0163303 991.587 <2e-16 ***
ORIGIN_GRID_ID1524 16.4420063 0.0101342 1622.421 <2e-16 ***
ORIGIN_GRID_ID1527 16.0883396 0.0164850 975.935 <2e-16 ***
ORIGIN_GRID_ID1535 12.2434959 0.0995245 123.020 <2e-16 ***
ORIGIN_GRID_ID1536 13.1802005 0.0354148 372.166 <2e-16 ***
ORIGIN_GRID_ID1537 13.7677207 0.0204361 673.697 <2e-16 ***
ORIGIN_GRID_ID1538 15.6460193 0.0070436 2221.295 <2e-16 ***
ORIGIN_GRID_ID1539 16.3084129 0.0056632 2879.710 <2e-16 ***
ORIGIN_GRID_ID1540 17.0921417 0.0047562 3593.636 <2e-16 ***
ORIGIN_GRID_ID1541 18.3381812 0.0054441 3368.480 <2e-16 ***
ORIGIN_GRID_ID1542 15.3549495 0.0162264 946.296 <2e-16 ***
ORIGIN_GRID_ID1543 15.7250557 0.0227133 692.327 <2e-16 ***
ORIGIN_GRID_ID1544 17.1444750 0.0068910 2487.947 <2e-16 ***
ORIGIN_GRID_ID1547 14.0056556 0.0601250 232.942 <2e-16 ***
ORIGIN_GRID_ID1556 13.7095272 0.0690394 198.575 <2e-16 ***
ORIGIN_GRID_ID1557 13.0924658 0.0375859 348.335 <2e-16 ***
ORIGIN_GRID_ID1558 14.4348160 0.0208252 693.141 <2e-16 ***
ORIGIN_GRID_ID1559 16.3774031 0.0053873 3039.994 <2e-16 ***
ORIGIN_GRID_ID1560 17.3669471 0.0040707 4266.310 <2e-16 ***
ORIGIN_GRID_ID1561 17.6669439 0.0049460 3571.945 <2e-16 ***
ORIGIN_GRID_ID1562 14.5776067 0.0215927 675.118 <2e-16 ***
ORIGIN_GRID_ID1563 16.2170025 0.0077688 2087.440 <2e-16 ***
ORIGIN_GRID_ID1564 15.4144384 0.0141615 1088.477 <2e-16 ***
ORIGIN_GRID_ID1565 15.4673872 0.0145814 1060.762 <2e-16 ***
ORIGIN_GRID_ID1566 14.9905399 0.0207187 723.527 <2e-16 ***
ORIGIN_GRID_ID1567 12.9283753 0.0949381 136.177 <2e-16 ***
ORIGIN_GRID_ID1568 13.4973341 0.0676055 199.648 <2e-16 ***
ORIGIN_GRID_ID1578 10.7215729 0.2582064 41.523 <2e-16 ***
ORIGIN_GRID_ID1580 14.9315293 0.0176876 844.182 <2e-16 ***
ORIGIN_GRID_ID1581 13.8667996 0.0220037 630.203 <2e-16 ***
ORIGIN_GRID_ID1582 17.1926288 0.0043122 3986.958 <2e-16 ***
ORIGIN_GRID_ID1583 15.8697812 0.0215027 738.037 <2e-16 ***
ORIGIN_GRID_ID1584 15.9259055 0.0110296 1443.919 <2e-16 ***
ORIGIN_GRID_ID1585 16.2662291 0.0098906 1644.621 <2e-16 ***
ORIGIN_GRID_ID1586 15.3857108 0.0139686 1101.449 <2e-16 ***
ORIGIN_GRID_ID1589 13.1633758 0.0953700 138.024 <2e-16 ***
ORIGIN_GRID_ID1590 13.7151319 0.0647231 211.905 <2e-16 ***
ORIGIN_GRID_ID1600 17.0402672 0.0101674 1675.975 <2e-16 ***
ORIGIN_GRID_ID1601 15.5921631 0.0081666 1909.254 <2e-16 ***
ORIGIN_GRID_ID1602 16.5973515 0.0065355 2539.563 <2e-16 ***
ORIGIN_GRID_ID1603 17.4668065 0.0043839 3984.345 <2e-16 ***
ORIGIN_GRID_ID1604 15.9327713 0.0084334 1889.236 <2e-16 ***
ORIGIN_GRID_ID1605 17.2962230 0.0046310 3734.909 <2e-16 ***
ORIGIN_GRID_ID1606 16.9589203 0.0098877 1715.150 <2e-16 ***
ORIGIN_GRID_ID1607 16.0681785 0.0098525 1630.874 <2e-16 ***
ORIGIN_GRID_ID1608 17.6616624 0.0047841 3691.707 <2e-16 ***
ORIGIN_GRID_ID1609 17.4120196 0.0059158 2943.309 <2e-16 ***
ORIGIN_GRID_ID1610 14.0500756 0.0668518 210.167 <2e-16 ***
ORIGIN_GRID_ID1622 15.7369051 0.0222517 707.223 <2e-16 ***
ORIGIN_GRID_ID1623 17.0134069 0.0045000 3780.782 <2e-16 ***
ORIGIN_GRID_ID1624 15.9496736 0.0086613 1841.494 <2e-16 ***
ORIGIN_GRID_ID1625 17.2864863 0.0050297 3436.912 <2e-16 ***
ORIGIN_GRID_ID1626 17.8498499 0.0037362 4777.528 <2e-16 ***
ORIGIN_GRID_ID1627 16.2568186 0.0075834 2143.743 <2e-16 ***
ORIGIN_GRID_ID1628 18.0448017 0.0037912 4759.637 <2e-16 ***
ORIGIN_GRID_ID1629 16.8999825 0.0070165 2408.594 <2e-16 ***
ORIGIN_GRID_ID1630 16.7781171 0.0078550 2135.990 <2e-16 ***
ORIGIN_GRID_ID1631 13.2619819 0.0700486 189.326 <2e-16 ***
ORIGIN_GRID_ID1642 14.7417189 0.0303857 485.153 <2e-16 ***
ORIGIN_GRID_ID1643 16.9176692 0.0047608 3553.509 <2e-16 ***
ORIGIN_GRID_ID1644 14.9943997 0.0173132 866.068 <2e-16 ***
ORIGIN_GRID_ID1645 16.5331049 0.0065140 2538.091 <2e-16 ***
ORIGIN_GRID_ID1646 16.4381957 0.0094467 1740.094 <2e-16 ***
ORIGIN_GRID_ID1647 16.5754316 0.0062269 2661.903 <2e-16 ***
ORIGIN_GRID_ID1648 17.1438261 0.0051681 3317.233 <2e-16 ***
ORIGIN_GRID_ID1649 17.8845447 0.0040183 4450.748 <2e-16 ***
ORIGIN_GRID_ID1650 17.6056897 0.0055003 3200.834 <2e-16 ***
ORIGIN_GRID_ID1664 11.9456906 0.1474548 81.013 <2e-16 ***
ORIGIN_GRID_ID1665 17.2002316 0.0043673 3938.404 <2e-16 ***
ORIGIN_GRID_ID1666 15.9511981 0.0075778 2105.003 <2e-16 ***
ORIGIN_GRID_ID1667 17.1679009 0.0108660 1579.967 <2e-16 ***
ORIGIN_GRID_ID1668 17.1958622 0.0050283 3419.841 <2e-16 ***
ORIGIN_GRID_ID1670 18.0232104 0.0038052 4736.446 <2e-16 ***
ORIGIN_GRID_ID1671 18.5711663 0.0053218 3489.613 <2e-16 ***
ORIGIN_GRID_ID1672 17.7091215 0.0058681 3017.866 <2e-16 ***
ORIGIN_GRID_ID1684 16.2402466 0.0136837 1186.833 <2e-16 ***
ORIGIN_GRID_ID1685 16.8033423 0.0056981 2948.955 <2e-16 ***
ORIGIN_GRID_ID1686 16.6172008 0.0057506 2889.638 <2e-16 ***
ORIGIN_GRID_ID1687 16.5727944 0.0078184 2119.729 <2e-16 ***
ORIGIN_GRID_ID1688 15.9079817 0.0090870 1750.633 <2e-16 ***
ORIGIN_GRID_ID1689 15.3592142 0.0135673 1132.073 <2e-16 ***
ORIGIN_GRID_ID1690 17.0182105 0.0068140 2497.527 <2e-16 ***
ORIGIN_GRID_ID1691 17.5767656 0.0047111 3730.960 <2e-16 ***
ORIGIN_GRID_ID1692 16.7067605 0.0084889 1968.077 <2e-16 ***
ORIGIN_GRID_ID1706 16.7106709 0.0067574 2472.926 <2e-16 ***
ORIGIN_GRID_ID1707 16.6527324 0.0054149 3075.339 <2e-16 ***
ORIGIN_GRID_ID1708 17.3063446 0.0044667 3874.490 <2e-16 ***
ORIGIN_GRID_ID1709 16.4438791 0.0069541 2364.627 <2e-16 ***
ORIGIN_GRID_ID1710 17.5864646 0.0045656 3851.979 <2e-16 ***
ORIGIN_GRID_ID1711 17.1971235 0.0055127 3119.533 <2e-16 ***
ORIGIN_GRID_ID1712 17.8885158 0.0038073 4698.476 <2e-16 ***
ORIGIN_GRID_ID1713 15.3684881 0.0136553 1125.463 <2e-16 ***
ORIGIN_GRID_ID1714 17.7922322 0.0049462 3597.138 <2e-16 ***
ORIGIN_GRID_ID1727 16.9185543 0.0056667 2985.613 <2e-16 ***
ORIGIN_GRID_ID1728 16.8640214 0.0053069 3177.756 <2e-16 ***
ORIGIN_GRID_ID1729 16.5043793 0.0062160 2655.163 <2e-16 ***
ORIGIN_GRID_ID1730 14.6043880 0.0233136 626.432 <2e-16 ***
ORIGIN_GRID_ID1731 17.1932182 0.0054978 3127.314 <2e-16 ***
ORIGIN_GRID_ID1732 17.6248846 0.0041180 4279.964 <2e-16 ***
ORIGIN_GRID_ID1733 17.3395525 0.0048293 3590.507 <2e-16 ***
ORIGIN_GRID_ID1734 17.4964950 0.0046067 3798.077 <2e-16 ***
ORIGIN_GRID_ID1735 18.5457998 0.0060267 3077.292 <2e-16 ***
ORIGIN_GRID_ID1748 15.6891218 0.0106341 1475.358 <2e-16 ***
ORIGIN_GRID_ID1749 16.6255204 0.0056018 2967.893 <2e-16 ***
ORIGIN_GRID_ID1750 15.8546909 0.0080381 1972.440 <2e-16 ***
ORIGIN_GRID_ID1751 15.8119782 0.0112838 1401.297 <2e-16 ***
ORIGIN_GRID_ID1753 17.7286519 0.0042432 4178.145 <2e-16 ***
ORIGIN_GRID_ID1754 17.9275946 0.0037679 4757.977 <2e-16 ***
ORIGIN_GRID_ID1755 17.3876350 0.0047086 3692.727 <2e-16 ***
ORIGIN_GRID_ID1756 17.1734819 0.0056600 3034.198 <2e-16 ***
ORIGIN_GRID_ID1757 14.5609929 0.0337145 431.892 <2e-16 ***
ORIGIN_GRID_ID1769 16.5145240 0.0065237 2531.459 <2e-16 ***
ORIGIN_GRID_ID1770 16.4279451 0.0107957 1521.705 <2e-16 ***
ORIGIN_GRID_ID1771 15.4806031 0.0116475 1329.094 <2e-16 ***
ORIGIN_GRID_ID1772 15.1618583 0.0268464 564.764 <2e-16 ***
ORIGIN_GRID_ID1774 17.3784729 0.0046924 3703.571 <2e-16 ***
ORIGIN_GRID_ID1775 16.8858748 0.0058853 2869.171 <2e-16 ***
ORIGIN_GRID_ID1776 17.8828697 0.0038200 4681.381 <2e-16 ***
ORIGIN_GRID_ID1777 17.9367257 0.0041922 4278.576 <2e-16 ***
ORIGIN_GRID_ID1778 16.9610565 0.0117121 1448.165 <2e-16 ***
ORIGIN_GRID_ID1790 17.1599064 0.0054573 3144.392 <2e-16 ***
ORIGIN_GRID_ID1791 16.5226781 0.0070442 2345.585 <2e-16 ***
ORIGIN_GRID_ID1792 16.7573008 0.0072385 2315.029 <2e-16 ***
ORIGIN_GRID_ID1793 14.9503445 0.0158613 942.566 <2e-16 ***
ORIGIN_GRID_ID1794 15.5166802 0.0286320 541.935 <2e-16 ***
ORIGIN_GRID_ID1795 14.2179727 0.0344504 412.709 <2e-16 ***
ORIGIN_GRID_ID1796 17.6887965 0.0046808 3778.979 <2e-16 ***
ORIGIN_GRID_ID1797 17.6377270 0.0042642 4136.197 <2e-16 ***
ORIGIN_GRID_ID1798 17.7618715 0.0042251 4203.930 <2e-16 ***
ORIGIN_GRID_ID1799 16.7347581 0.0078381 2135.056 <2e-16 ***
ORIGIN_GRID_ID1800 15.9139633 0.0265268 599.919 <2e-16 ***
ORIGIN_GRID_ID1811 16.3265047 0.0079796 2046.018 <2e-16 ***
ORIGIN_GRID_ID1812 17.5363625 0.0041014 4275.727 <2e-16 ***
ORIGIN_GRID_ID1813 17.4803467 0.0043221 4044.428 <2e-16 ***
ORIGIN_GRID_ID1817 17.4046523 0.0056016 3107.092 <2e-16 ***
ORIGIN_GRID_ID1818 17.4024360 0.0047728 3646.165 <2e-16 ***
ORIGIN_GRID_ID1819 17.7516641 0.0040487 4384.498 <2e-16 ***
ORIGIN_GRID_ID1820 14.5429233 0.0363774 399.779 <2e-16 ***
ORIGIN_GRID_ID1832 16.9918414 0.0059903 2836.553 <2e-16 ***
ORIGIN_GRID_ID1833 16.5634751 0.0064880 2552.927 <2e-16 ***
ORIGIN_GRID_ID1834 17.1286333 0.0049709 3445.770 <2e-16 ***
ORIGIN_GRID_ID1835 16.4744891 0.0079186 2080.487 <2e-16 ***
ORIGIN_GRID_ID1837 13.7909177 0.0631546 218.368 <2e-16 ***
ORIGIN_GRID_ID1839 16.7016871 0.0075914 2200.091 <2e-16 ***
ORIGIN_GRID_ID1840 18.6155323 0.0031874 5840.301 <2e-16 ***
ORIGIN_GRID_ID1841 13.7476322 0.0459751 299.024 <2e-16 ***
ORIGIN_GRID_ID1842 17.4599058 0.0111597 1564.548 <2e-16 ***
ORIGIN_GRID_ID1853 16.9803539 0.0054162 3135.093 <2e-16 ***
ORIGIN_GRID_ID1854 17.2667290 0.0051568 3348.325 <2e-16 ***
ORIGIN_GRID_ID1855 17.6152231 0.0045682 3856.030 <2e-16 ***
ORIGIN_GRID_ID1858 15.3430007 0.0269860 568.555 <2e-16 ***
ORIGIN_GRID_ID1860 17.8148427 0.0087529 2035.303 <2e-16 ***
ORIGIN_GRID_ID1861 17.6160009 0.0048608 3624.123 <2e-16 ***
ORIGIN_GRID_ID1874 17.1555776 0.0065730 2609.989 <2e-16 ***
ORIGIN_GRID_ID1875 15.6028889 0.0138283 1128.332 <2e-16 ***
ORIGIN_GRID_ID1876 17.4748482 0.0107271 1629.043 <2e-16 ***
ORIGIN_GRID_ID1877 17.2579247 0.0051887 3326.046 <2e-16 ***
ORIGIN_GRID_ID1880 14.1065455 0.0491327 287.111 <2e-16 ***
ORIGIN_GRID_ID1882 17.5252812 0.0052468 3340.166 <2e-16 ***
ORIGIN_GRID_ID1883 17.3244583 0.0090043 1924.021 <2e-16 ***
ORIGIN_GRID_ID1895 17.2265804 0.0052229 3298.261 <2e-16 ***
ORIGIN_GRID_ID1896 15.8061184 0.0102111 1547.928 <2e-16 ***
ORIGIN_GRID_ID1897 16.6051103 0.0094885 1750.027 <2e-16 ***
ORIGIN_GRID_ID1898 11.9843546 0.1507710 79.487 <2e-16 ***
ORIGIN_GRID_ID1901 13.8386384 0.0723913 191.164 <2e-16 ***
ORIGIN_GRID_ID1903 16.7870790 0.0090239 1860.299 <2e-16 ***
ORIGIN_GRID_ID1917 15.8695861 0.0102075 1554.698 <2e-16 ***
ORIGIN_GRID_ID1918 17.7189166 0.0061181 2896.151 <2e-16 ***
ORIGIN_GRID_ID1919 17.2087751 0.0055861 3080.648 <2e-16 ***
ORIGIN_GRID_ID1922 15.2010650 0.0280634 541.669 <2e-16 ***
ORIGIN_GRID_ID1924 16.7233120 0.0097072 1722.767 <2e-16 ***
ORIGIN_GRID_ID1937 16.6225828 0.0074525 2230.458 <2e-16 ***
ORIGIN_GRID_ID1938 17.4944166 0.0048113 3636.139 <2e-16 ***
ORIGIN_GRID_ID1939 18.0933128 0.0043488 4160.484 <2e-16 ***
ORIGIN_GRID_ID1942 14.3074983 0.0461753 309.852 <2e-16 ***
ORIGIN_GRID_ID1959 16.2873324 0.0092413 1762.442 <2e-16 ***
ORIGIN_GRID_ID1960 18.2506869 0.0033462 5454.136 <2e-16 ***
ORIGIN_GRID_ID1961 16.9455599 0.0073774 2296.942 <2e-16 ***
ORIGIN_GRID_ID1962 17.9410127 0.0046903 3825.126 <2e-16 ***
ORIGIN_GRID_ID1964 13.6039997 0.0860906 158.020 <2e-16 ***
ORIGIN_GRID_ID1979 16.5736988 0.0085545 1937.421 <2e-16 ***
ORIGIN_GRID_ID1980 15.0920900 0.0149639 1008.567 <2e-16 ***
ORIGIN_GRID_ID1981 17.6093789 0.0046439 3791.967 <2e-16 ***
ORIGIN_GRID_ID1982 16.4667384 0.0117804 1397.809 <2e-16 ***
ORIGIN_GRID_ID1983 17.9681583 0.0046930 3828.683 <2e-16 ***
ORIGIN_GRID_ID1984 16.6494089 0.0080795 2060.707 <2e-16 ***
ORIGIN_GRID_ID1985 17.2333541 0.0065924 2614.126 <2e-16 ***
ORIGIN_GRID_ID2001 16.8722947 0.0063542 2655.278 <2e-16 ***
ORIGIN_GRID_ID2002 17.6305485 0.0042095 4188.294 <2e-16 ***
ORIGIN_GRID_ID2003 17.2625982 0.0054243 3182.439 <2e-16 ***
ORIGIN_GRID_ID2004 18.0125664 0.0045306 3975.730 <2e-16 ***
ORIGIN_GRID_ID2005 17.8848248 0.0044458 4022.838 <2e-16 ***
ORIGIN_GRID_ID2006 16.4417102 0.0098549 1668.377 <2e-16 ***
ORIGIN_GRID_ID2007 15.8425104 0.0168033 942.822 <2e-16 ***
ORIGIN_GRID_ID2022 17.4693179 0.0063346 2757.747 <2e-16 ***
ORIGIN_GRID_ID2023 17.8820958 0.0040690 4394.707 <2e-16 ***
ORIGIN_GRID_ID2024 17.2338351 0.0051956 3316.975 <2e-16 ***
ORIGIN_GRID_ID2025 17.4459895 0.0049281 3540.071 <2e-16 ***
ORIGIN_GRID_ID2026 16.1069911 0.0120815 1333.195 <2e-16 ***
ORIGIN_GRID_ID2027 18.0959185 0.0042944 4213.799 <2e-16 ***
ORIGIN_GRID_ID2043 16.6558709 0.0081739 2037.692 <2e-16 ***
ORIGIN_GRID_ID2044 17.5775586 0.0046008 3820.532 <2e-16 ***
ORIGIN_GRID_ID2045 13.5290756 0.0785966 172.133 <2e-16 ***
ORIGIN_GRID_ID2046 17.4867404 0.0043033 4063.553 <2e-16 ***
ORIGIN_GRID_ID2047 17.4667435 0.0054870 3183.282 <2e-16 ***
ORIGIN_GRID_ID2048 17.6715407 0.0049084 3600.248 <2e-16 ***
ORIGIN_GRID_ID2049 16.6505705 0.0138835 1199.309 <2e-16 ***
ORIGIN_GRID_ID2064 17.4789834 0.0052699 3316.751 <2e-16 ***
ORIGIN_GRID_ID2065 16.0806469 0.0091132 1764.548 <2e-16 ***
ORIGIN_GRID_ID2066 15.5872704 0.0257032 606.434 <2e-16 ***
ORIGIN_GRID_ID2067 18.6106224 0.0031346 5937.201 <2e-16 ***
ORIGIN_GRID_ID2068 17.5981756 0.0072359 2432.064 <2e-16 ***
ORIGIN_GRID_ID2069 17.5010051 0.0057676 3034.351 <2e-16 ***
ORIGIN_GRID_ID2085 16.2311790 0.0101896 1592.917 <2e-16 ***
ORIGIN_GRID_ID2086 17.7942191 0.0043900 4053.387 <2e-16 ***
ORIGIN_GRID_ID2087 16.4906135 0.0078047 2112.921 <2e-16 ***
ORIGIN_GRID_ID2088 17.1741847 0.0049791 3449.288 <2e-16 ***
ORIGIN_GRID_ID2089 16.9402135 0.0068061 2488.991 <2e-16 ***
ORIGIN_GRID_ID2090 18.1563196 0.0038254 4746.306 <2e-16 ***
ORIGIN_GRID_ID2091 13.8239818 0.0739505 186.936 <2e-16 ***
ORIGIN_GRID_ID2105 14.1510857 0.1147345 123.338 <2e-16 ***
ORIGIN_GRID_ID2106 14.7787524 0.0204112 724.050 <2e-16 ***
ORIGIN_GRID_ID2107 15.8629959 0.0098732 1606.671 <2e-16 ***
ORIGIN_GRID_ID2108 17.1283624 0.0059326 2887.144 <2e-16 ***
ORIGIN_GRID_ID2109 17.3767315 0.0048308 3597.086 <2e-16 ***
ORIGIN_GRID_ID2110 16.9195199 0.0077046 2196.038 <2e-16 ***
ORIGIN_GRID_ID2111 14.4832785 0.0497912 290.880 <2e-16 ***
ORIGIN_GRID_ID2128 15.6580378 0.0152375 1027.596 <2e-16 ***
ORIGIN_GRID_ID2129 15.1671280 0.0163639 926.865 <2e-16 ***
ORIGIN_GRID_ID2130 17.6634446 0.0042148 4190.812 <2e-16 ***
ORIGIN_GRID_ID2131 17.9533778 0.0047522 3777.942 <2e-16 ***
ORIGIN_GRID_ID2132 17.1112833 0.0064275 2662.214 <2e-16 ***
ORIGIN_GRID_ID2148 16.4593844 0.0121707 1352.376 <2e-16 ***
ORIGIN_GRID_ID2149 15.1648086 0.0168152 901.849 <2e-16 ***
ORIGIN_GRID_ID2150 17.5813150 0.0048983 3589.260 <2e-16 ***
ORIGIN_GRID_ID2151 18.0480729 0.0038068 4741.071 <2e-16 ***
ORIGIN_GRID_ID2152 18.1774238 0.0041190 4413.068 <2e-16 ***
ORIGIN_GRID_ID2153 17.6747470 0.0057815 3057.128 <2e-16 ***
ORIGIN_GRID_ID2171 16.5487847 0.0076360 2167.219 <2e-16 ***
ORIGIN_GRID_ID2172 16.8124609 0.0082330 2042.090 <2e-16 ***
ORIGIN_GRID_ID2173 17.2071210 0.0054591 3151.991 <2e-16 ***
ORIGIN_GRID_ID2174 17.5770662 0.0055297 3178.650 <2e-16 ***
ORIGIN_GRID_ID2191 16.4582602 0.0107546 1530.351 <2e-16 ***
ORIGIN_GRID_ID2192 15.9553056 0.0117985 1352.321 <2e-16 ***
ORIGIN_GRID_ID2193 17.0589534 0.0063619 2681.432 <2e-16 ***
ORIGIN_GRID_ID2194 17.3664368 0.0054722 3173.592 <2e-16 ***
ORIGIN_GRID_ID2195 16.6830344 0.0221835 752.046 <2e-16 ***
ORIGIN_GRID_ID2212 13.8374670 0.1037196 133.412 <2e-16 ***
ORIGIN_GRID_ID2213 13.5981439 0.0447679 303.748 <2e-16 ***
ORIGIN_GRID_ID2214 15.0710213 0.0279073 540.040 <2e-16 ***
ORIGIN_GRID_ID2215 17.0150053 0.0072109 2359.616 <2e-16 ***
ORIGIN_GRID_ID2216 16.1751818 0.0113881 1420.358 <2e-16 ***
ORIGIN_GRID_ID2233 13.8770866 0.0494280 280.753 <2e-16 ***
ORIGIN_GRID_ID2234 16.4554960 0.0205505 800.733 <2e-16 ***
ORIGIN_GRID_ID2235 15.9357271 0.0138952 1146.855 <2e-16 ***
ORIGIN_GRID_ID2236 16.0088813 0.0132172 1211.220 <2e-16 ***
ORIGIN_GRID_ID2237 13.6692554 0.0618131 221.139 <2e-16 ***
ORIGIN_GRID_ID2256 14.4613530 0.0444165 325.585 <2e-16 ***
ORIGIN_GRID_ID2257 15.5209071 0.0204204 760.070 <2e-16 ***
ORIGIN_GRID_ID2258 15.2268448 0.0167371 909.767 <2e-16 ***
ORIGIN_GRID_ID2259 14.7700400 0.0397063 371.982 <2e-16 ***
ORIGIN_GRID_ID2277 15.3482819 0.0382686 401.067 <2e-16 ***
ORIGIN_GRID_ID2278 15.9566759 0.0163345 976.868 <2e-16 ***
ORIGIN_GRID_ID2279 15.1218838 0.0206652 731.755 <2e-16 ***
ORIGIN_GRID_ID2280 12.7999662 0.1336460 95.775 <2e-16 ***
ORIGIN_GRID_ID2297 17.3252873 0.0100197 1729.120 <2e-16 ***
ORIGIN_GRID_ID2300 13.5051087 0.0698759 193.273 <2e-16 ***
ORIGIN_GRID_ID2301 15.2142853 0.0201731 754.188 <2e-16 ***
ORIGIN_GRID_ID2318 15.7236853 0.0198828 790.817 <2e-16 ***
ORIGIN_GRID_ID2319 16.6162927 0.0114566 1450.366 <2e-16 ***
ORIGIN_GRID_ID2322 16.3025195 0.0129778 1256.188 <2e-16 ***
ORIGIN_GRID_ID2337 17.4349870 0.0156568 1113.575 <2e-16 ***
ORIGIN_GRID_ID2341 16.8702873 0.0105872 1593.465 <2e-16 ***
ORIGIN_GRID_ID2343 15.9912596 0.0148211 1078.953 <2e-16 ***
ORIGIN_GRID_ID2361 16.6906912 0.0128903 1294.827 <2e-16 ***
ORIGIN_GRID_ID2364 13.0995296 0.0958082 136.727 <2e-16 ***
ORIGIN_GRID_ID2379 17.1667440 0.0168255 1020.282 <2e-16 ***
ORIGIN_GRID_ID2384 16.2730598 0.0175037 929.690 <2e-16 ***
ORIGIN_GRID_ID2405 15.8866309 0.0183550 865.521 <2e-16 ***
ORIGIN_GRID_ID2406 14.6037091 0.0399331 365.705 <2e-16 ***
ORIGIN_GRID_ID2426 16.2377027 0.0332909 487.752 <2e-16 ***
ORIGIN_GRID_ID2427 17.1517378 0.0116141 1476.804 <2e-16 ***
ORIGIN_GRID_ID2505 16.6735991 0.0460454 362.112 <2e-16 ***
log(DESTIN_TRAIN_EXIT_CT) 0.4851972 0.0004390 1105.326 <2e-16 ***
log(DESTIN_PRESCHOOL_CT) 0.0088319 0.0003486 25.338 <2e-16 ***
log(DESTIN_BUSINESS_CT) 0.0691203 0.0001998 345.933 <2e-16 ***
log(DESTIN_FINSERV_CT) 0.2429692 0.0002983 814.437 <2e-16 ***
log(DESTIN_SCH_CT) 0.2783567 0.0007329 379.827 <2e-16 ***
log(dist) -1.5029925 0.0002895 -5192.577 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 278704584 on 62186 degrees of freedom
Residual deviance: 30620057 on 61363 degrees of freedom
AIC: 30957807
Number of Fisher Scoring iterations: 7Destination Constrained SIM output
The R-squared value of 0.37 tells us that the explanatory variables are able to explain 37% of the variance in the TRIPS target variable.
Adjusted_squared
All the coefficients are statistically significant (refer to next tab).
The most influential explanatory variables are distance, origin 5 room count and origin exec count count with coefficients of -1.42, 0.09 and 0.04 respectively.
Call:
glm(formula = TRIPS ~ DESTIN_GRID_ID + log(ORIGIN_RENTAL_CT) +
log(ORIGIN_2ROOM_CT) + log(ORIGIN_3ROOM_CT) + log(ORIGIN_4ROOM_CT) +
log(ORIGIN_5ROOM_CT) + log(ORIGIN_EXEC_CT) + log(ORIGIN_STUDIO_CT) +
log(dist) - 1, family = poisson(link = "log"), data = flow_data1,
na.action = na.exclude)
Deviance Residuals:
Min 1Q Median 3Q Max
-368.58 -11.61 -5.26 0.79 606.65
Coefficients:
Estimate Std. Error z value Pr(>|z|)
DESTIN_GRID_ID23 1.604e+01 5.527e-02 290.28 <2e-16 ***
DESTIN_GRID_ID44 1.730e+01 2.343e-02 738.09 <2e-16 ***
DESTIN_GRID_ID46 1.637e+01 2.049e-02 798.91 <2e-16 ***
DESTIN_GRID_ID66 1.545e+01 4.879e-02 316.67 <2e-16 ***
DESTIN_GRID_ID67 1.634e+01 1.448e-02 1128.20 <2e-16 ***
DESTIN_GRID_ID68 1.651e+01 2.054e-02 803.82 <2e-16 ***
DESTIN_GRID_ID86 1.644e+01 3.644e-02 451.21 <2e-16 ***
DESTIN_GRID_ID87 1.419e+01 8.773e-02 161.79 <2e-16 ***
DESTIN_GRID_ID88 1.593e+01 1.828e-02 871.60 <2e-16 ***
DESTIN_GRID_ID89 1.625e+01 2.104e-02 772.55 <2e-16 ***
DESTIN_GRID_ID90 1.180e+01 7.071e-01 16.68 <2e-16 ***
DESTIN_GRID_ID109 1.608e+01 2.498e-02 643.92 <2e-16 ***
DESTIN_GRID_ID110 1.253e+01 1.179e-01 106.34 <2e-16 ***
DESTIN_GRID_ID111 1.642e+01 1.276e-02 1287.49 <2e-16 ***
DESTIN_GRID_ID112 1.443e+01 3.362e-02 429.10 <2e-16 ***
DESTIN_GRID_ID128 1.609e+01 2.522e-02 637.87 <2e-16 ***
DESTIN_GRID_ID129 1.315e+01 1.374e-01 95.75 <2e-16 ***
DESTIN_GRID_ID130 1.551e+01 2.343e-02 661.69 <2e-16 ***
DESTIN_GRID_ID131 1.506e+01 2.252e-02 668.86 <2e-16 ***
DESTIN_GRID_ID132 1.631e+01 1.541e-02 1058.11 <2e-16 ***
DESTIN_GRID_ID133 1.596e+01 1.291e-02 1236.27 <2e-16 ***
DESTIN_GRID_ID134 1.613e+01 1.208e-02 1334.98 <2e-16 ***
DESTIN_GRID_ID150 1.575e+01 2.640e-02 596.78 <2e-16 ***
DESTIN_GRID_ID151 1.533e+01 2.297e-02 667.47 <2e-16 ***
DESTIN_GRID_ID152 1.680e+01 1.461e-02 1150.00 <2e-16 ***
DESTIN_GRID_ID153 1.657e+01 1.356e-02 1222.09 <2e-16 ***
DESTIN_GRID_ID154 1.466e+01 2.834e-02 517.33 <2e-16 ***
DESTIN_GRID_ID155 1.527e+01 1.987e-02 768.45 <2e-16 ***
DESTIN_GRID_ID156 1.605e+01 2.114e-02 759.12 <2e-16 ***
DESTIN_GRID_ID172 1.444e+01 4.499e-02 320.90 <2e-16 ***
DESTIN_GRID_ID174 1.603e+01 1.505e-02 1064.73 <2e-16 ***
DESTIN_GRID_ID175 1.599e+01 1.118e-02 1430.70 <2e-16 ***
DESTIN_GRID_ID176 1.447e+01 2.781e-02 520.29 <2e-16 ***
DESTIN_GRID_ID195 1.549e+01 3.065e-02 505.36 <2e-16 ***
DESTIN_GRID_ID196 1.617e+01 1.041e-02 1553.23 <2e-16 ***
DESTIN_GRID_ID197 1.318e+01 7.718e-02 170.82 <2e-16 ***
DESTIN_GRID_ID215 1.612e+01 2.993e-02 538.53 <2e-16 ***
DESTIN_GRID_ID216 1.540e+01 1.612e-02 955.09 <2e-16 ***
DESTIN_GRID_ID217 1.674e+01 9.444e-03 1773.03 <2e-16 ***
DESTIN_GRID_ID237 1.576e+01 3.064e-02 514.47 <2e-16 ***
DESTIN_GRID_ID238 1.602e+01 1.521e-02 1053.51 <2e-16 ***
DESTIN_GRID_ID239 1.521e+01 3.143e-02 484.04 <2e-16 ***
DESTIN_GRID_ID257 1.615e+01 1.567e-02 1031.06 <2e-16 ***
DESTIN_GRID_ID258 1.541e+01 1.933e-02 796.97 <2e-16 ***
DESTIN_GRID_ID259 1.657e+01 1.212e-02 1366.41 <2e-16 ***
DESTIN_GRID_ID278 1.641e+01 1.402e-02 1170.70 <2e-16 ***
DESTIN_GRID_ID279 1.617e+01 1.345e-02 1201.99 <2e-16 ***
DESTIN_GRID_ID280 1.640e+01 1.265e-02 1296.83 <2e-16 ***
DESTIN_GRID_ID298 1.303e+01 1.508e-01 86.45 <2e-16 ***
DESTIN_GRID_ID299 1.662e+01 1.640e-02 1013.09 <2e-16 ***
DESTIN_GRID_ID300 1.529e+01 1.725e-02 886.32 <2e-16 ***
DESTIN_GRID_ID320 1.711e+01 1.397e-02 1224.95 <2e-16 ***
DESTIN_GRID_ID321 1.551e+01 2.392e-02 648.31 <2e-16 ***
DESTIN_GRID_ID322 1.742e+01 1.188e-02 1466.26 <2e-16 ***
DESTIN_GRID_ID340 1.758e+01 1.092e-02 1609.31 <2e-16 ***
DESTIN_GRID_ID341 1.644e+01 1.235e-02 1330.60 <2e-16 ***
DESTIN_GRID_ID342 1.698e+01 1.059e-02 1603.61 <2e-16 ***
DESTIN_GRID_ID363 1.670e+01 1.334e-02 1251.67 <2e-16 ***
DESTIN_GRID_ID364 1.781e+01 7.937e-03 2243.98 <2e-16 ***
DESTIN_GRID_ID383 1.678e+01 9.138e-03 1836.27 <2e-16 ***
DESTIN_GRID_ID384 1.733e+01 8.474e-03 2045.61 <2e-16 ***
DESTIN_GRID_ID385 1.678e+01 1.521e-02 1103.36 <2e-16 ***
DESTIN_GRID_ID404 1.742e+01 1.260e-02 1382.55 <2e-16 ***
DESTIN_GRID_ID405 1.713e+01 1.054e-02 1625.21 <2e-16 ***
DESTIN_GRID_ID406 1.660e+01 5.475e-03 3032.03 <2e-16 ***
DESTIN_GRID_ID407 1.679e+01 9.625e-03 1744.81 <2e-16 ***
DESTIN_GRID_ID408 1.769e+01 5.291e-03 3343.97 <2e-16 ***
DESTIN_GRID_ID425 1.517e+01 2.491e-02 608.80 <2e-16 ***
DESTIN_GRID_ID426 1.637e+01 1.034e-02 1582.20 <2e-16 ***
DESTIN_GRID_ID427 1.343e+01 2.652e-02 506.59 <2e-16 ***
DESTIN_GRID_ID428 1.573e+01 1.174e-02 1340.46 <2e-16 ***
DESTIN_GRID_ID429 1.534e+01 2.384e-02 643.58 <2e-16 ***
DESTIN_GRID_ID446 1.608e+01 2.314e-02 694.99 <2e-16 ***
DESTIN_GRID_ID447 1.556e+01 1.720e-02 904.29 <2e-16 ***
DESTIN_GRID_ID448 1.597e+01 1.178e-02 1356.11 <2e-16 ***
DESTIN_GRID_ID449 1.603e+01 7.431e-03 2156.80 <2e-16 ***
DESTIN_GRID_ID450 1.529e+01 1.273e-02 1201.63 <2e-16 ***
DESTIN_GRID_ID468 1.622e+01 1.099e-02 1475.19 <2e-16 ***
DESTIN_GRID_ID469 1.545e+01 8.716e-03 1773.15 <2e-16 ***
DESTIN_GRID_ID470 1.571e+01 7.603e-03 2066.81 <2e-16 ***
DESTIN_GRID_ID471 1.539e+01 1.726e-02 891.64 <2e-16 ***
DESTIN_GRID_ID488 1.551e+01 2.218e-02 699.09 <2e-16 ***
DESTIN_GRID_ID489 1.403e+01 4.805e-02 291.92 <2e-16 ***
DESTIN_GRID_ID490 1.621e+01 8.929e-03 1815.31 <2e-16 ***
DESTIN_GRID_ID491 1.396e+01 1.688e-02 826.62 <2e-16 ***
DESTIN_GRID_ID493 1.330e+01 4.890e-02 271.88 <2e-16 ***
DESTIN_GRID_ID494 1.521e+01 2.318e-02 656.09 <2e-16 ***
DESTIN_GRID_ID509 1.547e+01 1.530e-02 1011.18 <2e-16 ***
DESTIN_GRID_ID510 1.621e+01 1.021e-02 1587.56 <2e-16 ***
DESTIN_GRID_ID511 1.569e+01 7.144e-03 2195.66 <2e-16 ***
DESTIN_GRID_ID512 1.545e+01 7.234e-03 2135.89 <2e-16 ***
DESTIN_GRID_ID513 1.634e+01 8.248e-03 1981.23 <2e-16 ***
DESTIN_GRID_ID514 1.596e+01 1.189e-02 1342.41 <2e-16 ***
DESTIN_GRID_ID515 1.474e+01 3.197e-02 461.17 <2e-16 ***
DESTIN_GRID_ID530 1.516e+01 2.905e-02 521.73 <2e-16 ***
DESTIN_GRID_ID531 1.737e+01 6.207e-03 2798.10 <2e-16 ***
DESTIN_GRID_ID532 1.590e+01 9.108e-03 1746.11 <2e-16 ***
DESTIN_GRID_ID533 1.721e+01 3.532e-03 4873.02 <2e-16 ***
DESTIN_GRID_ID534 1.561e+01 7.265e-03 2148.99 <2e-16 ***
DESTIN_GRID_ID536 1.500e+01 1.834e-02 817.45 <2e-16 ***
DESTIN_GRID_ID537 1.469e+01 3.473e-02 423.14 <2e-16 ***
DESTIN_GRID_ID538 1.413e+01 4.421e-02 319.60 <2e-16 ***
DESTIN_GRID_ID539 1.284e+01 2.673e-01 48.06 <2e-16 ***
DESTIN_GRID_ID551 1.581e+01 1.775e-02 890.80 <2e-16 ***
DESTIN_GRID_ID552 1.757e+01 1.085e-02 1619.88 <2e-16 ***
DESTIN_GRID_ID553 1.536e+01 8.925e-03 1720.72 <2e-16 ***
DESTIN_GRID_ID554 1.534e+01 7.378e-03 2078.81 <2e-16 ***
DESTIN_GRID_ID555 1.628e+01 7.888e-03 2064.17 <2e-16 ***
DESTIN_GRID_ID559 1.455e+01 5.374e-02 270.72 <2e-16 ***
DESTIN_GRID_ID560 1.612e+01 1.683e-02 957.44 <2e-16 ***
DESTIN_GRID_ID561 1.451e+01 6.762e-02 214.57 <2e-16 ***
DESTIN_GRID_ID572 1.577e+01 3.451e-02 456.82 <2e-16 ***
DESTIN_GRID_ID573 1.677e+01 1.041e-02 1611.42 <2e-16 ***
DESTIN_GRID_ID574 1.616e+01 1.581e-02 1022.21 <2e-16 ***
DESTIN_GRID_ID575 1.783e+01 2.804e-03 6357.69 <2e-16 ***
DESTIN_GRID_ID576 1.565e+01 6.710e-03 2331.83 <2e-16 ***
DESTIN_GRID_ID578 1.230e+01 1.072e-01 114.70 <2e-16 ***
DESTIN_GRID_ID582 1.381e+01 6.316e-02 218.60 <2e-16 ***
DESTIN_GRID_ID583 1.270e+01 3.780e-01 33.61 <2e-16 ***
DESTIN_GRID_ID584 1.549e+01 3.615e-02 428.44 <2e-16 ***
DESTIN_GRID_ID593 1.454e+01 2.564e-02 567.09 <2e-16 ***
DESTIN_GRID_ID594 1.601e+01 1.390e-02 1151.60 <2e-16 ***
DESTIN_GRID_ID595 1.638e+01 6.158e-03 2660.34 <2e-16 ***
DESTIN_GRID_ID596 1.582e+01 5.472e-03 2891.40 <2e-16 ***
DESTIN_GRID_ID597 1.532e+01 1.559e-02 982.10 <2e-16 ***
DESTIN_GRID_ID603 1.393e+01 5.275e-02 264.17 <2e-16 ***
DESTIN_GRID_ID604 1.504e+01 5.084e-02 295.81 <2e-16 ***
DESTIN_GRID_ID615 1.501e+01 1.486e-02 1010.57 <2e-16 ***
DESTIN_GRID_ID616 1.592e+01 9.253e-03 1720.92 <2e-16 ***
DESTIN_GRID_ID617 1.495e+01 9.380e-03 1594.14 <2e-16 ***
DESTIN_GRID_ID618 1.537e+01 7.070e-03 2173.89 <2e-16 ***
DESTIN_GRID_ID620 1.607e+01 1.104e-02 1455.60 <2e-16 ***
DESTIN_GRID_ID637 1.556e+01 1.105e-02 1407.89 <2e-16 ***
DESTIN_GRID_ID638 1.544e+01 6.506e-03 2372.71 <2e-16 ***
DESTIN_GRID_ID657 1.639e+01 7.258e-03 2258.91 <2e-16 ***
DESTIN_GRID_ID658 1.581e+01 6.478e-03 2440.97 <2e-16 ***
DESTIN_GRID_ID659 1.576e+01 6.124e-03 2574.16 <2e-16 ***
DESTIN_GRID_ID660 1.615e+01 4.781e-03 3378.76 <2e-16 ***
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DESTIN_GRID_ID1689 1.447e+01 1.066e-02 1357.76 <2e-16 ***
DESTIN_GRID_ID1690 1.395e+01 1.403e-02 994.18 <2e-16 ***
DESTIN_GRID_ID1691 1.605e+01 4.703e-03 3411.62 <2e-16 ***
DESTIN_GRID_ID1692 1.399e+01 1.542e-02 906.90 <2e-16 ***
DESTIN_GRID_ID1706 1.548e+01 8.330e-03 1858.53 <2e-16 ***
DESTIN_GRID_ID1707 1.460e+01 9.099e-03 1604.21 <2e-16 ***
DESTIN_GRID_ID1708 1.518e+01 7.102e-03 2138.02 <2e-16 ***
DESTIN_GRID_ID1709 1.597e+01 5.166e-03 3091.73 <2e-16 ***
DESTIN_GRID_ID1710 1.594e+01 5.445e-03 2926.67 <2e-16 ***
DESTIN_GRID_ID1711 1.650e+01 4.074e-03 4050.35 <2e-16 ***
DESTIN_GRID_ID1712 1.570e+01 4.959e-03 3165.92 <2e-16 ***
DESTIN_GRID_ID1713 1.339e+01 1.678e-02 797.95 <2e-16 ***
DESTIN_GRID_ID1714 1.491e+01 9.035e-03 1650.31 <2e-16 ***
DESTIN_GRID_ID1727 1.600e+01 6.057e-03 2641.94 <2e-16 ***
DESTIN_GRID_ID1728 1.589e+01 5.127e-03 3098.44 <2e-16 ***
DESTIN_GRID_ID1729 1.602e+01 4.870e-03 3289.92 <2e-16 ***
DESTIN_GRID_ID1730 1.517e+01 8.609e-03 1761.75 <2e-16 ***
DESTIN_GRID_ID1731 1.611e+01 4.957e-03 3249.84 <2e-16 ***
DESTIN_GRID_ID1732 1.552e+01 5.386e-03 2881.32 <2e-16 ***
DESTIN_GRID_ID1733 1.451e+01 9.057e-03 1602.53 <2e-16 ***
DESTIN_GRID_ID1734 1.579e+01 5.228e-03 3021.10 <2e-16 ***
DESTIN_GRID_ID1735 1.507e+01 1.621e-02 929.45 <2e-16 ***
DESTIN_GRID_ID1748 1.502e+01 9.884e-03 1519.78 <2e-16 ***
DESTIN_GRID_ID1749 1.605e+01 4.698e-03 3416.29 <2e-16 ***
DESTIN_GRID_ID1750 1.601e+01 4.821e-03 3320.26 <2e-16 ***
DESTIN_GRID_ID1751 1.561e+01 6.712e-03 2325.42 <2e-16 ***
DESTIN_GRID_ID1753 1.597e+01 4.927e-03 3241.16 <2e-16 ***
DESTIN_GRID_ID1754 1.694e+01 3.202e-03 5290.69 <2e-16 ***
DESTIN_GRID_ID1755 1.634e+01 3.974e-03 4111.72 <2e-16 ***
DESTIN_GRID_ID1756 1.544e+01 6.060e-03 2547.21 <2e-16 ***
DESTIN_GRID_ID1757 1.409e+01 2.292e-02 614.95 <2e-16 ***
DESTIN_GRID_ID1769 1.574e+01 6.524e-03 2412.63 <2e-16 ***
DESTIN_GRID_ID1770 1.526e+01 8.790e-03 1735.65 <2e-16 ***
DESTIN_GRID_ID1771 1.605e+01 5.575e-03 2879.84 <2e-16 ***
DESTIN_GRID_ID1772 1.699e+01 7.206e-03 2357.30 <2e-16 ***
DESTIN_GRID_ID1774 1.508e+01 7.472e-03 2018.19 <2e-16 ***
DESTIN_GRID_ID1775 1.468e+01 8.267e-03 1776.09 <2e-16 ***
DESTIN_GRID_ID1776 1.690e+01 3.232e-03 5229.08 <2e-16 ***
DESTIN_GRID_ID1777 1.519e+01 7.548e-03 2012.99 <2e-16 ***
DESTIN_GRID_ID1778 1.433e+01 2.277e-02 629.45 <2e-16 ***
DESTIN_GRID_ID1790 1.620e+01 5.807e-03 2790.40 <2e-16 ***
DESTIN_GRID_ID1791 1.556e+01 7.011e-03 2218.84 <2e-16 ***
DESTIN_GRID_ID1792 1.575e+01 7.572e-03 2080.57 <2e-16 ***
DESTIN_GRID_ID1793 1.574e+01 6.226e-03 2528.39 <2e-16 ***
DESTIN_GRID_ID1794 1.726e+01 7.601e-03 2270.50 <2e-16 ***
DESTIN_GRID_ID1795 1.351e+01 2.150e-02 628.15 <2e-16 ***
DESTIN_GRID_ID1796 1.569e+01 5.697e-03 2754.47 <2e-16 ***
DESTIN_GRID_ID1797 1.535e+01 5.938e-03 2585.39 <2e-16 ***
DESTIN_GRID_ID1798 1.569e+01 5.606e-03 2799.64 <2e-16 ***
DESTIN_GRID_ID1799 1.492e+01 9.297e-03 1604.39 <2e-16 ***
DESTIN_GRID_ID1800 1.288e+01 6.472e-02 198.97 <2e-16 ***
DESTIN_GRID_ID1811 1.537e+01 8.933e-03 1720.96 <2e-16 ***
DESTIN_GRID_ID1812 1.649e+01 3.947e-03 4178.31 <2e-16 ***
DESTIN_GRID_ID1813 1.670e+01 3.739e-03 4465.45 <2e-16 ***
DESTIN_GRID_ID1817 1.395e+01 1.411e-02 988.36 <2e-16 ***
DESTIN_GRID_ID1818 1.531e+01 6.138e-03 2493.47 <2e-16 ***
DESTIN_GRID_ID1819 1.698e+01 3.261e-03 5206.82 <2e-16 ***
DESTIN_GRID_ID1820 1.275e+01 5.042e-02 252.79 <2e-16 ***
DESTIN_GRID_ID1832 1.654e+01 5.085e-03 3252.90 <2e-16 ***
DESTIN_GRID_ID1833 1.517e+01 7.810e-03 1942.35 <2e-16 ***
DESTIN_GRID_ID1834 1.510e+01 7.234e-03 2087.57 <2e-16 ***
DESTIN_GRID_ID1835 1.521e+01 8.002e-03 1900.29 <2e-16 ***
DESTIN_GRID_ID1837 1.523e+01 1.421e-02 1071.85 <2e-16 ***
DESTIN_GRID_ID1839 1.406e+01 1.373e-02 1024.27 <2e-16 ***
DESTIN_GRID_ID1840 1.680e+01 3.609e-03 4655.62 <2e-16 ***
DESTIN_GRID_ID1841 1.349e+01 2.815e-02 478.99 <2e-16 ***
DESTIN_GRID_ID1842 1.501e+01 1.635e-02 917.85 <2e-16 ***
DESTIN_GRID_ID1853 1.573e+01 6.265e-03 2510.22 <2e-16 ***
DESTIN_GRID_ID1854 1.588e+01 5.650e-03 2810.28 <2e-16 ***
DESTIN_GRID_ID1855 1.611e+01 5.019e-03 3210.46 <2e-16 ***
DESTIN_GRID_ID1858 1.626e+01 8.546e-03 1902.06 <2e-16 ***
DESTIN_GRID_ID1860 1.462e+01 2.210e-02 661.29 <2e-16 ***
DESTIN_GRID_ID1861 1.568e+01 6.196e-03 2530.11 <2e-16 ***
DESTIN_GRID_ID1874 1.538e+01 1.072e-02 1435.36 <2e-16 ***
DESTIN_GRID_ID1875 1.363e+01 2.393e-02 569.73 <2e-16 ***
DESTIN_GRID_ID1876 1.503e+01 2.466e-02 609.64 <2e-16 ***
DESTIN_GRID_ID1877 1.589e+01 5.419e-03 2931.40 <2e-16 ***
DESTIN_GRID_ID1880 1.538e+01 1.418e-02 1084.55 <2e-16 ***
DESTIN_GRID_ID1882 1.552e+01 6.747e-03 2300.62 <2e-16 ***
DESTIN_GRID_ID1883 1.430e+01 2.159e-02 662.21 <2e-16 ***
DESTIN_GRID_ID1895 1.618e+01 5.497e-03 2943.06 <2e-16 ***
DESTIN_GRID_ID1896 1.513e+01 8.235e-03 1836.96 <2e-16 ***
DESTIN_GRID_ID1897 1.431e+01 1.317e-02 1086.27 <2e-16 ***
DESTIN_GRID_ID1898 1.400e+01 2.562e-02 546.23 <2e-16 ***
DESTIN_GRID_ID1901 1.479e+01 2.049e-02 721.74 <2e-16 ***
DESTIN_GRID_ID1903 1.402e+01 1.924e-02 728.75 <2e-16 ***
DESTIN_GRID_ID1917 1.500e+01 9.991e-03 1501.45 <2e-16 ***
DESTIN_GRID_ID1918 1.626e+01 6.988e-03 2326.40 <2e-16 ***
DESTIN_GRID_ID1919 1.610e+01 5.132e-03 3138.09 <2e-16 ***
DESTIN_GRID_ID1922 1.592e+01 1.076e-02 1480.05 <2e-16 ***
DESTIN_GRID_ID1924 1.359e+01 2.390e-02 568.84 <2e-16 ***
DESTIN_GRID_ID1937 1.557e+01 8.086e-03 1925.45 <2e-16 ***
DESTIN_GRID_ID1938 1.627e+01 4.959e-03 3282.20 <2e-16 ***
DESTIN_GRID_ID1939 1.499e+01 9.518e-03 1574.44 <2e-16 ***
DESTIN_GRID_ID1942 1.478e+01 1.917e-02 770.97 <2e-16 ***
DESTIN_GRID_ID1959 1.506e+01 1.043e-02 1443.83 <2e-16 ***
DESTIN_GRID_ID1960 1.729e+01 3.035e-03 5698.23 <2e-16 ***
DESTIN_GRID_ID1961 1.479e+01 1.033e-02 1432.69 <2e-16 ***
DESTIN_GRID_ID1962 1.563e+01 6.467e-03 2417.39 <2e-16 ***
DESTIN_GRID_ID1964 1.649e+01 1.132e-02 1457.28 <2e-16 ***
DESTIN_GRID_ID1979 1.556e+01 8.714e-03 1785.62 <2e-16 ***
DESTIN_GRID_ID1980 1.542e+01 7.279e-03 2118.41 <2e-16 ***
DESTIN_GRID_ID1981 1.532e+01 7.707e-03 1987.46 <2e-16 ***
DESTIN_GRID_ID1982 1.562e+01 8.174e-03 1911.21 <2e-16 ***
DESTIN_GRID_ID1983 1.559e+01 6.572e-03 2371.80 <2e-16 ***
DESTIN_GRID_ID1984 1.564e+01 6.480e-03 2414.28 <2e-16 ***
DESTIN_GRID_ID1985 1.587e+01 6.142e-03 2583.15 <2e-16 ***
DESTIN_GRID_ID2001 1.546e+01 7.174e-03 2154.97 <2e-16 ***
DESTIN_GRID_ID2002 1.553e+01 5.840e-03 2659.43 <2e-16 ***
DESTIN_GRID_ID2003 1.607e+01 4.850e-03 3313.65 <2e-16 ***
DESTIN_GRID_ID2004 1.635e+01 4.675e-03 3497.95 <2e-16 ***
DESTIN_GRID_ID2005 1.532e+01 7.023e-03 2181.90 <2e-16 ***
DESTIN_GRID_ID2006 1.639e+01 5.016e-03 3267.64 <2e-16 ***
DESTIN_GRID_ID2007 1.313e+01 3.310e-02 396.71 <2e-16 ***
DESTIN_GRID_ID2022 1.612e+01 7.067e-03 2281.44 <2e-16 ***
DESTIN_GRID_ID2023 1.600e+01 5.153e-03 3104.95 <2e-16 ***
DESTIN_GRID_ID2024 1.627e+01 4.352e-03 3738.09 <2e-16 ***
DESTIN_GRID_ID2025 1.506e+01 7.347e-03 2050.34 <2e-16 ***
DESTIN_GRID_ID2026 1.431e+01 1.287e-02 1112.42 <2e-16 ***
DESTIN_GRID_ID2027 1.635e+01 4.735e-03 3452.30 <2e-16 ***
DESTIN_GRID_ID2043 1.454e+01 1.264e-02 1150.76 <2e-16 ***
DESTIN_GRID_ID2044 1.554e+01 6.447e-03 2410.83 <2e-16 ***
DESTIN_GRID_ID2045 1.478e+01 1.249e-02 1183.57 <2e-16 ***
DESTIN_GRID_ID2046 1.625e+01 4.129e-03 3935.75 <2e-16 ***
DESTIN_GRID_ID2047 1.442e+01 1.039e-02 1387.35 <2e-16 ***
DESTIN_GRID_ID2048 1.472e+01 9.469e-03 1554.84 <2e-16 ***
DESTIN_GRID_ID2049 1.312e+01 3.038e-02 431.85 <2e-16 ***
DESTIN_GRID_ID2064 1.544e+01 7.658e-03 2015.69 <2e-16 ***
DESTIN_GRID_ID2065 1.535e+01 7.612e-03 2016.43 <2e-16 ***
DESTIN_GRID_ID2066 1.287e+01 3.802e-02 338.68 <2e-16 ***
DESTIN_GRID_ID2067 1.760e+01 2.746e-03 6407.07 <2e-16 ***
DESTIN_GRID_ID2068 1.441e+01 1.541e-02 934.96 <2e-16 ***
DESTIN_GRID_ID2069 1.493e+01 9.458e-03 1578.97 <2e-16 ***
DESTIN_GRID_ID2085 1.558e+01 7.805e-03 1995.80 <2e-16 ***
DESTIN_GRID_ID2086 1.675e+01 4.146e-03 4039.40 <2e-16 ***
DESTIN_GRID_ID2087 1.642e+01 4.414e-03 3719.37 <2e-16 ***
DESTIN_GRID_ID2088 1.529e+01 6.250e-03 2447.01 <2e-16 ***
DESTIN_GRID_ID2089 1.493e+01 9.514e-03 1568.94 <2e-16 ***
DESTIN_GRID_ID2090 1.739e+01 3.081e-03 5644.56 <2e-16 ***
DESTIN_GRID_ID2091 1.242e+01 7.110e-02 174.64 <2e-16 ***
DESTIN_GRID_ID2105 1.531e+01 6.656e-02 230.03 <2e-16 ***
DESTIN_GRID_ID2106 1.410e+01 1.579e-02 893.37 <2e-16 ***
DESTIN_GRID_ID2107 1.668e+01 4.218e-03 3954.57 <2e-16 ***
DESTIN_GRID_ID2108 1.627e+01 5.105e-03 3186.90 <2e-16 ***
DESTIN_GRID_ID2109 1.492e+01 7.423e-03 2010.44 <2e-16 ***
DESTIN_GRID_ID2110 1.448e+01 1.265e-02 1144.62 <2e-16 ***
DESTIN_GRID_ID2111 1.342e+01 3.624e-02 370.26 <2e-16 ***
DESTIN_GRID_ID2128 1.601e+01 8.675e-03 1845.86 <2e-16 ***
DESTIN_GRID_ID2129 1.536e+01 1.119e-02 1372.91 <2e-16 ***
DESTIN_GRID_ID2130 1.536e+01 6.062e-03 2533.24 <2e-16 ***
DESTIN_GRID_ID2131 1.532e+01 7.881e-03 1944.04 <2e-16 ***
DESTIN_GRID_ID2132 1.507e+01 8.574e-03 1758.31 <2e-16 ***
DESTIN_GRID_ID2148 1.490e+01 1.696e-02 878.50 <2e-16 ***
DESTIN_GRID_ID2149 1.495e+01 1.173e-02 1274.38 <2e-16 ***
DESTIN_GRID_ID2150 1.497e+01 9.548e-03 1567.44 <2e-16 ***
DESTIN_GRID_ID2151 1.677e+01 3.503e-03 4788.76 <2e-16 ***
DESTIN_GRID_ID2152 1.577e+01 5.804e-03 2717.34 <2e-16 ***
DESTIN_GRID_ID2153 1.460e+01 1.254e-02 1164.02 <2e-16 ***
DESTIN_GRID_ID2171 1.594e+01 6.186e-03 2576.53 <2e-16 ***
DESTIN_GRID_ID2172 1.434e+01 1.230e-02 1166.15 <2e-16 ***
DESTIN_GRID_ID2173 1.492e+01 7.986e-03 1867.91 <2e-16 ***
DESTIN_GRID_ID2174 1.568e+01 6.998e-03 2240.30 <2e-16 ***
DESTIN_GRID_ID2191 1.617e+01 8.567e-03 1887.83 <2e-16 ***
DESTIN_GRID_ID2192 1.497e+01 1.165e-02 1284.64 <2e-16 ***
DESTIN_GRID_ID2193 1.564e+01 6.768e-03 2310.89 <2e-16 ***
DESTIN_GRID_ID2194 1.564e+01 6.245e-03 2504.81 <2e-16 ***
DESTIN_GRID_ID2195 1.424e+01 4.116e-02 345.95 <2e-16 ***
DESTIN_GRID_ID2212 1.698e+01 1.407e-02 1206.39 <2e-16 ***
DESTIN_GRID_ID2213 1.594e+01 9.247e-03 1723.57 <2e-16 ***
DESTIN_GRID_ID2214 1.684e+01 7.262e-03 2318.34 <2e-16 ***
DESTIN_GRID_ID2215 1.485e+01 1.044e-02 1421.59 <2e-16 ***
DESTIN_GRID_ID2216 1.589e+01 6.386e-03 2488.35 <2e-16 ***
DESTIN_GRID_ID2233 1.672e+01 1.028e-02 1627.23 <2e-16 ***
DESTIN_GRID_ID2234 1.712e+01 8.503e-03 2013.55 <2e-16 ***
DESTIN_GRID_ID2235 1.594e+01 9.511e-03 1675.99 <2e-16 ***
DESTIN_GRID_ID2236 1.442e+01 1.420e-02 1016.15 <2e-16 ***
DESTIN_GRID_ID2237 1.588e+01 1.171e-02 1356.83 <2e-16 ***
DESTIN_GRID_ID2256 1.619e+01 1.275e-02 1269.79 <2e-16 ***
DESTIN_GRID_ID2257 1.356e+01 2.944e-02 460.62 <2e-16 ***
DESTIN_GRID_ID2258 1.562e+01 7.658e-03 2039.64 <2e-16 ***
DESTIN_GRID_ID2259 1.668e+01 1.060e-02 1573.21 <2e-16 ***
DESTIN_GRID_ID2277 1.514e+01 2.654e-02 570.26 <2e-16 ***
DESTIN_GRID_ID2278 1.494e+01 1.752e-02 852.68 <2e-16 ***
DESTIN_GRID_ID2279 1.570e+01 7.858e-03 1997.57 <2e-16 ***
DESTIN_GRID_ID2280 1.430e+01 3.439e-02 415.98 <2e-16 ***
DESTIN_GRID_ID2297 1.468e+01 2.098e-02 699.93 <2e-16 ***
DESTIN_GRID_ID2300 1.479e+01 2.102e-02 703.92 <2e-16 ***
DESTIN_GRID_ID2301 1.537e+01 1.031e-02 1490.31 <2e-16 ***
DESTIN_GRID_ID2318 1.705e+01 6.178e-03 2760.07 <2e-16 ***
DESTIN_GRID_ID2319 1.702e+01 5.840e-03 2913.85 <2e-16 ***
DESTIN_GRID_ID2322 1.562e+01 1.031e-02 1515.27 <2e-16 ***
DESTIN_GRID_ID2337 1.666e+01 1.732e-02 962.05 <2e-16 ***
DESTIN_GRID_ID2341 1.719e+01 5.862e-03 2932.55 <2e-16 ***
DESTIN_GRID_ID2343 1.485e+01 1.442e-02 1029.80 <2e-16 ***
DESTIN_GRID_ID2361 1.599e+01 1.007e-02 1588.36 <2e-16 ***
DESTIN_GRID_ID2364 1.356e+01 3.639e-02 372.54 <2e-16 ***
DESTIN_GRID_ID2379 1.590e+01 2.599e-02 611.64 <2e-16 ***
DESTIN_GRID_ID2384 1.681e+01 7.203e-03 2333.55 <2e-16 ***
DESTIN_GRID_ID2405 1.752e+01 5.096e-03 3438.79 <2e-16 ***
DESTIN_GRID_ID2406 1.450e+01 2.430e-02 596.84 <2e-16 ***
DESTIN_GRID_ID2426 1.689e+01 1.136e-02 1486.09 <2e-16 ***
DESTIN_GRID_ID2427 1.709e+01 7.125e-03 2398.48 <2e-16 ***
DESTIN_GRID_ID2505 1.724e+01 1.953e-02 882.70 <2e-16 ***
log(ORIGIN_RENTAL_CT) 2.062e-03 9.502e-05 21.70 <2e-16 ***
log(ORIGIN_2ROOM_CT) 1.330e-02 1.169e-04 113.76 <2e-16 ***
log(ORIGIN_3ROOM_CT) 1.176e-02 9.481e-05 124.07 <2e-16 ***
log(ORIGIN_4ROOM_CT) 3.754e-02 1.885e-04 199.18 <2e-16 ***
log(ORIGIN_5ROOM_CT) 9.368e-02 1.920e-04 488.01 <2e-16 ***
log(ORIGIN_EXEC_CT) 4.111e-02 9.666e-05 425.35 <2e-16 ***
log(ORIGIN_STUDIO_CT) 6.473e-03 1.422e-04 45.51 <2e-16 ***
log(dist) -1.412e+00 2.871e-04 -4917.90 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 278704584 on 62186 degrees of freedom
Residual deviance: 31288107 on 61360 degrees of freedom
AIC: 31625863
Number of Fisher Scoring iterations: 8Doubly Constrained SIM Output
The R-squared value of 0.58 tells us that the explanatory variables are able to explain 58 % of the variance in the TRIPS target variable.
Adjusted R-squared of 0.57 is the highest for this model.
The explanatory variable ‘distance’ is statistically significant and has a coefficient of -0.158.
Call:
glm(formula = TRIPS ~ ORIGIN_GRID_ID + DESTIN_GRID_ID + log(dist),
family = poisson(link = "log"), data = flow_data1, na.action = na.exclude)
Deviance Residuals:
Min 1Q Median 3Q Max
-218.08 -8.98 -3.09 2.56 386.13
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 14.4394926 0.1405168 102.760 < 2e-16 ***
ORIGIN_GRID_ID44 1.7000385 0.2004115 8.483 < 2e-16 ***
ORIGIN_GRID_ID46 -0.1447060 0.1618108 -0.894 0.371166
ORIGIN_GRID_ID66 1.4035649 0.1872598 7.495 6.62e-14 ***
ORIGIN_GRID_ID67 1.7876519 0.1317456 13.569 < 2e-16 ***
ORIGIN_GRID_ID68 -0.6420455 0.1732983 -3.705 0.000212 ***
ORIGIN_GRID_ID86 -0.4732650 0.1543778 -3.066 0.002172 **
ORIGIN_GRID_ID87 3.3340486 0.1505693 22.143 < 2e-16 ***
ORIGIN_GRID_ID88 2.3754367 0.1304699 18.207 < 2e-16 ***
ORIGIN_GRID_ID89 0.2039094 0.1389233 1.468 0.142163
ORIGIN_GRID_ID90 0.9054951 0.1837021 4.929 8.26e-07 ***
ORIGIN_GRID_ID109 0.3377856 0.1681050 2.009 0.044498 *
ORIGIN_GRID_ID110 0.5217344 0.1528227 3.414 0.000640 ***
ORIGIN_GRID_ID111 3.9109202 0.1300172 30.080 < 2e-16 ***
ORIGIN_GRID_ID112 0.1026062 0.1479722 0.693 0.488049
ORIGIN_GRID_ID128 3.0503331 0.1328095 22.968 < 2e-16 ***
ORIGIN_GRID_ID129 0.3418501 0.2293981 1.490 0.136171
ORIGIN_GRID_ID130 1.2646370 0.1413093 8.949 < 2e-16 ***
ORIGIN_GRID_ID131 1.8833836 0.1337129 14.085 < 2e-16 ***
ORIGIN_GRID_ID132 0.1695822 0.1412540 1.201 0.229926
ORIGIN_GRID_ID133 1.0766949 0.1360562 7.914 2.50e-15 ***
ORIGIN_GRID_ID134 4.1143202 0.1328106 30.979 < 2e-16 ***
ORIGIN_GRID_ID150 4.1682825 0.1311336 31.787 < 2e-16 ***
ORIGIN_GRID_ID151 0.4327500 0.1535129 2.819 0.004818 **
ORIGIN_GRID_ID152 0.2182047 0.1561780 1.397 0.162368
ORIGIN_GRID_ID153 1.4498776 0.1371608 10.571 < 2e-16 ***
ORIGIN_GRID_ID154 4.1273458 0.1295077 31.870 < 2e-16 ***
ORIGIN_GRID_ID155 0.9710493 0.1351553 7.185 6.74e-13 ***
ORIGIN_GRID_ID156 1.6880586 0.1406709 12.000 < 2e-16 ***
ORIGIN_GRID_ID172 2.3015222 0.1458894 15.776 < 2e-16 ***
ORIGIN_GRID_ID174 1.1003307 0.1381870 7.963 1.68e-15 ***
ORIGIN_GRID_ID175 3.8065984 0.1298011 29.326 < 2e-16 ***
ORIGIN_GRID_ID176 4.8230262 0.1293836 37.277 < 2e-16 ***
ORIGIN_GRID_ID195 -0.0902374 0.1564839 -0.577 0.564171
ORIGIN_GRID_ID196 0.9000050 0.1363245 6.602 4.06e-11 ***
ORIGIN_GRID_ID197 0.0723198 0.1861044 0.389 0.697573
ORIGIN_GRID_ID215 1.4442699 0.1628827 8.867 < 2e-16 ***
ORIGIN_GRID_ID216 5.2368269 0.1295104 40.436 < 2e-16 ***
ORIGIN_GRID_ID217 2.3643516 0.1312692 18.011 < 2e-16 ***
ORIGIN_GRID_ID237 0.4280936 0.3281514 1.305 0.192042
ORIGIN_GRID_ID238 0.8341390 0.1501996 5.554 2.80e-08 ***
ORIGIN_GRID_ID239 1.0987139 0.1939379 5.665 1.47e-08 ***
ORIGIN_GRID_ID257 0.2015634 0.1438810 1.401 0.161243
ORIGIN_GRID_ID258 2.2459656 0.1326372 16.933 < 2e-16 ***
ORIGIN_GRID_ID259 1.4768354 0.1358379 10.872 < 2e-16 ***
ORIGIN_GRID_ID278 1.6216420 0.1350863 12.004 < 2e-16 ***
ORIGIN_GRID_ID279 0.4173954 0.1383897 3.016 0.002561 **
ORIGIN_GRID_ID280 0.9417711 0.1389363 6.778 1.21e-11 ***
ORIGIN_GRID_ID298 -3.1159126 0.3996733 -7.796 6.38e-15 ***
ORIGIN_GRID_ID299 0.1391199 0.1426829 0.975 0.329546
ORIGIN_GRID_ID300 4.1733077 0.1297074 32.175 < 2e-16 ***
ORIGIN_GRID_ID320 -0.2671295 0.1396143 -1.913 0.055705 .
ORIGIN_GRID_ID321 0.8195822 0.1524845 5.375 7.66e-08 ***
ORIGIN_GRID_ID322 2.5744695 0.1357645 18.963 < 2e-16 ***
ORIGIN_GRID_ID340 1.9812589 0.1332422 14.870 < 2e-16 ***
ORIGIN_GRID_ID341 -0.1188257 0.1389854 -0.855 0.392578
ORIGIN_GRID_ID342 1.9972039 0.1363768 14.645 < 2e-16 ***
ORIGIN_GRID_ID363 1.5837570 0.1356049 11.679 < 2e-16 ***
ORIGIN_GRID_ID364 2.1499307 0.1323598 16.243 < 2e-16 ***
ORIGIN_GRID_ID383 1.0439561 0.1338266 7.801 6.15e-15 ***
ORIGIN_GRID_ID384 0.5072620 0.1397352 3.630 0.000283 ***
ORIGIN_GRID_ID385 0.8798587 0.1471742 5.978 2.25e-09 ***
ORIGIN_GRID_ID404 2.1421757 0.1331672 16.086 < 2e-16 ***
ORIGIN_GRID_ID405 0.5410149 0.1412063 3.831 0.000127 ***
ORIGIN_GRID_ID406 5.9825841 0.1294179 46.227 < 2e-16 ***
ORIGIN_GRID_ID407 1.9553941 0.1386956 14.098 < 2e-16 ***
ORIGIN_GRID_ID408 2.6963345 0.1319479 20.435 < 2e-16 ***
ORIGIN_GRID_ID425 -0.6413884 0.1660321 -3.863 0.000112 ***
ORIGIN_GRID_ID426 1.4841912 0.1331439 11.147 < 2e-16 ***
ORIGIN_GRID_ID427 0.6525150 0.1382567 4.720 2.36e-06 ***
ORIGIN_GRID_ID428 0.1200996 0.1799547 0.667 0.504524
ORIGIN_GRID_ID429 2.3272037 0.1312772 17.727 < 2e-16 ***
ORIGIN_GRID_ID446 0.9435815 0.1480985 6.371 1.87e-10 ***
ORIGIN_GRID_ID447 0.9058870 0.1358592 6.668 2.60e-11 ***
ORIGIN_GRID_ID448 1.9539424 0.1324629 14.751 < 2e-16 ***
ORIGIN_GRID_ID449 5.1692623 0.1295967 39.887 < 2e-16 ***
ORIGIN_GRID_ID450 2.1332501 0.1311140 16.270 < 2e-16 ***
ORIGIN_GRID_ID468 1.8043071 0.1335853 13.507 < 2e-16 ***
ORIGIN_GRID_ID469 3.1290065 0.1303635 24.002 < 2e-16 ***
ORIGIN_GRID_ID470 5.2192705 0.1295310 40.294 < 2e-16 ***
ORIGIN_GRID_ID471 2.9998349 0.1306774 22.956 < 2e-16 ***
ORIGIN_GRID_ID488 0.6436314 0.1425061 4.517 6.29e-06 ***
ORIGIN_GRID_ID489 -1.0712484 0.2130433 -5.028 4.95e-07 ***
ORIGIN_GRID_ID490 3.6202026 0.1300370 27.840 < 2e-16 ***
ORIGIN_GRID_ID491 4.1266490 0.1296803 31.822 < 2e-16 ***
ORIGIN_GRID_ID493 -1.6369434 0.2537581 -6.451 1.11e-10 ***
ORIGIN_GRID_ID494 0.7362184 0.1520294 4.843 1.28e-06 ***
ORIGIN_GRID_ID509 0.6642812 0.1352657 4.911 9.06e-07 ***
ORIGIN_GRID_ID510 1.4517745 0.1322779 10.975 < 2e-16 ***
ORIGIN_GRID_ID511 3.0296124 0.1299415 23.315 < 2e-16 ***
ORIGIN_GRID_ID512 5.7488376 0.1294710 44.403 < 2e-16 ***
ORIGIN_GRID_ID513 2.1569506 0.1323947 16.292 < 2e-16 ***
ORIGIN_GRID_ID514 1.3990989 0.1410002 9.923 < 2e-16 ***
ORIGIN_GRID_ID515 0.0010554 0.2585958 0.004 0.996744
ORIGIN_GRID_ID530 -0.2701643 0.1580648 -1.709 0.087414 .
ORIGIN_GRID_ID531 1.9411831 0.1311428 14.802 < 2e-16 ***
ORIGIN_GRID_ID532 1.3481497 0.1322603 10.193 < 2e-16 ***
ORIGIN_GRID_ID533 5.4178947 0.1294718 41.846 < 2e-16 ***
ORIGIN_GRID_ID534 6.0372357 0.1294849 46.625 < 2e-16 ***
ORIGIN_GRID_ID536 2.7627705 0.1323608 20.873 < 2e-16 ***
ORIGIN_GRID_ID537 0.4091371 0.2322685 1.761 0.078157 .
ORIGIN_GRID_ID538 0.3289687 0.2888638 1.139 0.254771
ORIGIN_GRID_ID539 0.1601534 1.0089940 0.159 0.873885
ORIGIN_GRID_ID551 -0.2263846 0.1415100 -1.600 0.109648
ORIGIN_GRID_ID552 2.2450404 0.1349684 16.634 < 2e-16 ***
ORIGIN_GRID_ID553 1.8095393 0.1307972 13.835 < 2e-16 ***
ORIGIN_GRID_ID554 5.3543280 0.1294794 41.353 < 2e-16 ***
ORIGIN_GRID_ID555 4.6170790 0.1296783 35.604 < 2e-16 ***
ORIGIN_GRID_ID559 1.1585255 0.1680187 6.895 5.38e-12 ***
ORIGIN_GRID_ID560 3.2696350 0.1414541 23.114 < 2e-16 ***
ORIGIN_GRID_ID561 -1.3495666 1.0097280 -1.337 0.181365
ORIGIN_GRID_ID572 -2.5401995 0.5919818 -4.291 1.78e-05 ***
ORIGIN_GRID_ID573 0.1262137 0.1380137 0.915 0.360453
ORIGIN_GRID_ID574 1.7515711 0.1349813 12.976 < 2e-16 ***
ORIGIN_GRID_ID575 6.3768468 0.1294498 49.261 < 2e-16 ***
ORIGIN_GRID_ID576 4.9721012 0.1295371 38.384 < 2e-16 ***
ORIGIN_GRID_ID578 0.3694284 0.1662829 2.222 0.026305 *
ORIGIN_GRID_ID582 0.6232556 0.1702506 3.661 0.000251 ***
ORIGIN_GRID_ID583 1.5675238 0.5918999 2.648 0.008090 **
ORIGIN_GRID_ID584 3.9655103 0.1421229 27.902 < 2e-16 ***
ORIGIN_GRID_ID593 1.3223490 0.1396717 9.468 < 2e-16 ***
ORIGIN_GRID_ID594 1.3975808 0.1321946 10.572 < 2e-16 ***
ORIGIN_GRID_ID595 1.6616695 0.1309860 12.686 < 2e-16 ***
ORIGIN_GRID_ID596 4.7129310 0.1295094 36.391 < 2e-16 ***
ORIGIN_GRID_ID597 1.9965206 0.1432526 13.937 < 2e-16 ***
ORIGIN_GRID_ID603 1.1721397 0.1754553 6.681 2.38e-11 ***
ORIGIN_GRID_ID604 1.6199767 0.2319517 6.984 2.87e-12 ***
ORIGIN_GRID_ID615 -0.0671903 0.1391070 -0.483 0.629087
ORIGIN_GRID_ID616 1.1209157 0.1336057 8.390 < 2e-16 ***
ORIGIN_GRID_ID617 2.0191588 0.1308812 15.427 < 2e-16 ***
ORIGIN_GRID_ID618 5.3999225 0.1294927 41.701 < 2e-16 ***
ORIGIN_GRID_ID620 2.7565738 0.1334273 20.660 < 2e-16 ***
ORIGIN_GRID_ID637 0.8310967 0.1372308 6.056 1.39e-09 ***
ORIGIN_GRID_ID638 4.8147666 0.1295087 37.177 < 2e-16 ***
ORIGIN_GRID_ID657 2.6568142 0.1306396 20.337 < 2e-16 ***
ORIGIN_GRID_ID658 4.1577664 0.1296106 32.079 < 2e-16 ***
ORIGIN_GRID_ID659 4.3723232 0.1295611 33.747 < 2e-16 ***
ORIGIN_GRID_ID660 5.4510183 0.1294852 42.098 < 2e-16 ***
ORIGIN_GRID_ID662 5.5815936 0.1296684 43.045 < 2e-16 ***
ORIGIN_GRID_ID677 2.5512438 0.1316680 19.376 < 2e-16 ***
ORIGIN_GRID_ID678 0.3533335 0.1388067 2.546 0.010912 *
ORIGIN_GRID_ID679 5.3756090 0.1294932 41.513 < 2e-16 ***
ORIGIN_GRID_ID680 5.6373410 0.1294921 43.534 < 2e-16 ***
ORIGIN_GRID_ID681 4.3790212 0.1297436 33.751 < 2e-16 ***
ORIGIN_GRID_ID699 2.0666820 0.1316461 15.699 < 2e-16 ***
ORIGIN_GRID_ID700 4.3627952 0.1295963 33.664 < 2e-16 ***
ORIGIN_GRID_ID701 4.2487350 0.1295992 32.784 < 2e-16 ***
ORIGIN_GRID_ID702 5.2979307 0.1294910 40.913 < 2e-16 ***
ORIGIN_GRID_ID704 2.4106822 0.1339708 17.994 < 2e-16 ***
ORIGIN_GRID_ID722 2.0230547 0.1310860 15.433 < 2e-16 ***
ORIGIN_GRID_ID725 1.9715960 0.1360899 14.487 < 2e-16 ***
ORIGIN_GRID_ID741 2.6288101 0.1305746 20.133 < 2e-16 ***
ORIGIN_GRID_ID743 2.8084937 0.1301480 21.579 < 2e-16 ***
ORIGIN_GRID_ID744 4.8371196 0.1295307 37.343 < 2e-16 ***
ORIGIN_GRID_ID761 2.0669575 0.1330306 15.537 < 2e-16 ***
ORIGIN_GRID_ID762 4.1343192 0.1296664 31.884 < 2e-16 ***
ORIGIN_GRID_ID763 1.2921140 0.1329859 9.716 < 2e-16 ***
ORIGIN_GRID_ID764 5.3551730 0.1294907 41.356 < 2e-16 ***
ORIGIN_GRID_ID765 4.6340052 0.1297368 35.719 < 2e-16 ***
ORIGIN_GRID_ID767 6.4784824 0.1295053 50.025 < 2e-16 ***
ORIGIN_GRID_ID772 1.1039120 0.1532364 7.204 5.85e-13 ***
ORIGIN_GRID_ID784 1.2170904 0.1325942 9.179 < 2e-16 ***
ORIGIN_GRID_ID785 4.5198585 0.1295211 34.897 < 2e-16 ***
ORIGIN_GRID_ID786 4.2290211 0.1295998 32.631 < 2e-16 ***
ORIGIN_GRID_ID787 4.8118592 0.1296705 37.108 < 2e-16 ***
ORIGIN_GRID_ID788 5.6919967 0.1295710 43.930 < 2e-16 ***
ORIGIN_GRID_ID789 4.1321764 0.1299379 31.801 < 2e-16 ***
ORIGIN_GRID_ID803 0.1041407 0.1447654 0.719 0.471909
ORIGIN_GRID_ID804 5.1555264 0.1295169 39.806 < 2e-16 ***
ORIGIN_GRID_ID805 5.1696129 0.1294904 39.923 < 2e-16 ***
ORIGIN_GRID_ID806 4.8499764 0.1295201 37.446 < 2e-16 ***
ORIGIN_GRID_ID807 5.8974360 0.1295228 45.532 < 2e-16 ***
ORIGIN_GRID_ID808 4.1108533 0.1299617 31.631 < 2e-16 ***
ORIGIN_GRID_ID809 5.8644044 0.1294967 45.286 < 2e-16 ***
ORIGIN_GRID_ID810 5.1073768 0.1295970 39.410 < 2e-16 ***
ORIGIN_GRID_ID814 3.0237247 0.1325439 22.813 < 2e-16 ***
ORIGIN_GRID_ID819 5.2044909 0.1310160 39.724 < 2e-16 ***
ORIGIN_GRID_ID824 1.2131666 0.1361827 8.908 < 2e-16 ***
ORIGIN_GRID_ID826 2.7928254 0.1298927 21.501 < 2e-16 ***
ORIGIN_GRID_ID827 4.7956964 0.1295082 37.030 < 2e-16 ***
ORIGIN_GRID_ID828 5.2050265 0.1295007 40.193 < 2e-16 ***
ORIGIN_GRID_ID829 5.2608639 0.1295331 40.614 < 2e-16 ***
ORIGIN_GRID_ID830 5.5537083 0.1295569 42.867 < 2e-16 ***
ORIGIN_GRID_ID831 6.3956996 0.1294808 49.395 < 2e-16 ***
ORIGIN_GRID_ID832 5.4858435 0.1296429 42.315 < 2e-16 ***
ORIGIN_GRID_ID835 2.9241291 0.1328928 22.004 < 2e-16 ***
ORIGIN_GRID_ID844 0.2995635 0.1512370 1.981 0.047619 *
ORIGIN_GRID_ID846 4.2047339 0.1295669 32.452 < 2e-16 ***
ORIGIN_GRID_ID847 3.2147711 0.1298669 24.754 < 2e-16 ***
ORIGIN_GRID_ID848 4.5745868 0.1295419 35.314 < 2e-16 ***
ORIGIN_GRID_ID849 3.8274038 0.1297005 29.510 < 2e-16 ***
ORIGIN_GRID_ID850 4.6759141 0.1295794 36.085 < 2e-16 ***
ORIGIN_GRID_ID851 5.2868309 0.1295187 40.819 < 2e-16 ***
ORIGIN_GRID_ID852 4.8244263 0.1296188 37.220 < 2e-16 ***
ORIGIN_GRID_ID853 6.8141686 0.1295285 52.608 < 2e-16 ***
ORIGIN_GRID_ID854 3.1979741 0.1321551 24.199 < 2e-16 ***
ORIGIN_GRID_ID855 1.7329059 0.1373024 12.621 < 2e-16 ***
ORIGIN_GRID_ID856 3.4020601 0.1309108 25.988 < 2e-16 ***
ORIGIN_GRID_ID866 2.1331690 0.1326331 16.083 < 2e-16 ***
ORIGIN_GRID_ID867 3.0466309 0.1300574 23.425 < 2e-16 ***
ORIGIN_GRID_ID868 2.0904108 0.1312943 15.922 < 2e-16 ***
ORIGIN_GRID_ID869 4.9929713 0.1295928 38.528 < 2e-16 ***
ORIGIN_GRID_ID870 5.7478461 0.1294789 44.392 < 2e-16 ***
ORIGIN_GRID_ID871 5.5571469 0.1296003 42.879 < 2e-16 ***
ORIGIN_GRID_ID872 3.4766127 0.1299902 26.745 < 2e-16 ***
ORIGIN_GRID_ID873 3.6908701 0.1299054 28.412 < 2e-16 ***
ORIGIN_GRID_ID874 4.0350862 0.1297229 31.105 < 2e-16 ***
ORIGIN_GRID_ID875 0.9326164 0.1470840 6.341 2.29e-10 ***
ORIGIN_GRID_ID876 2.1637190 0.1332827 16.234 < 2e-16 ***
ORIGIN_GRID_ID877 1.6099570 0.1364466 11.799 < 2e-16 ***
ORIGIN_GRID_ID887 2.4402124 0.1302387 18.736 < 2e-16 ***
ORIGIN_GRID_ID888 3.9027259 0.1296664 30.098 < 2e-16 ***
ORIGIN_GRID_ID889 0.8229380 0.1340861 6.137 8.39e-10 ***
ORIGIN_GRID_ID890 5.1919487 0.1295000 40.092 < 2e-16 ***
ORIGIN_GRID_ID891 3.9233256 0.1299888 30.182 < 2e-16 ***
ORIGIN_GRID_ID893 5.3400047 0.1295113 41.232 < 2e-16 ***
ORIGIN_GRID_ID894 3.5834988 0.1299033 27.586 < 2e-16 ***
ORIGIN_GRID_ID895 3.0867269 0.1304192 23.668 < 2e-16 ***
ORIGIN_GRID_ID896 1.8558622 0.1331805 13.935 < 2e-16 ***
ORIGIN_GRID_ID897 0.1004059 0.1496222 0.671 0.502180
ORIGIN_GRID_ID898 2.3710565 0.1337102 17.733 < 2e-16 ***
ORIGIN_GRID_ID908 3.9008951 0.1300987 29.984 < 2e-16 ***
ORIGIN_GRID_ID909 3.9088610 0.1295898 30.163 < 2e-16 ***
ORIGIN_GRID_ID910 2.0513082 0.1305997 15.707 < 2e-16 ***
ORIGIN_GRID_ID911 3.3426310 0.1297943 25.753 < 2e-16 ***
ORIGIN_GRID_ID912 4.9177569 0.1295194 37.969 < 2e-16 ***
ORIGIN_GRID_ID915 5.2349962 0.1295233 40.417 < 2e-16 ***
ORIGIN_GRID_ID917 4.7880616 0.1296687 36.925 < 2e-16 ***
ORIGIN_GRID_ID918 1.0928637 0.1360521 8.033 9.54e-16 ***
ORIGIN_GRID_ID919 4.2809051 0.1298003 32.981 < 2e-16 ***
ORIGIN_GRID_ID928 2.7461185 0.1303441 21.068 < 2e-16 ***
ORIGIN_GRID_ID929 4.3399173 0.1295308 33.505 < 2e-16 ***
ORIGIN_GRID_ID930 5.1857429 0.1294820 40.050 < 2e-16 ***
ORIGIN_GRID_ID931 2.1499270 0.1307374 16.445 < 2e-16 ***
ORIGIN_GRID_ID932 2.6751132 0.1307608 20.458 < 2e-16 ***
ORIGIN_GRID_ID933 4.7866598 0.1295802 36.940 < 2e-16 ***
ORIGIN_GRID_ID934 2.2459312 0.1310293 17.141 < 2e-16 ***
ORIGIN_GRID_ID935 6.1024596 0.1294800 47.131 < 2e-16 ***
ORIGIN_GRID_ID938 -1.8237896 0.3061117 -5.958 2.55e-09 ***
ORIGIN_GRID_ID939 6.0155975 0.1295226 46.444 < 2e-16 ***
ORIGIN_GRID_ID940 0.1113370 0.1603074 0.695 0.487355
ORIGIN_GRID_ID949 2.6006431 0.1302916 19.960 < 2e-16 ***
ORIGIN_GRID_ID950 4.7580462 0.1295514 36.727 < 2e-16 ***
ORIGIN_GRID_ID951 5.6181141 0.1294733 43.392 < 2e-16 ***
ORIGIN_GRID_ID952 2.3296815 0.1313921 17.731 < 2e-16 ***
ORIGIN_GRID_ID953 3.5024960 0.1298552 26.972 < 2e-16 ***
ORIGIN_GRID_ID954 2.3897088 0.1307481 18.277 < 2e-16 ***
ORIGIN_GRID_ID955 4.6526088 0.1295812 35.905 < 2e-16 ***
ORIGIN_GRID_ID956 3.0600450 0.1300303 23.533 < 2e-16 ***
ORIGIN_GRID_ID957 5.2444236 0.1295871 40.470 < 2e-16 ***
ORIGIN_GRID_ID959 1.2460318 0.1401454 8.891 < 2e-16 ***
ORIGIN_GRID_ID961 1.1948037 0.1343144 8.896 < 2e-16 ***
ORIGIN_GRID_ID962 6.3969950 0.1296705 49.333 < 2e-16 ***
ORIGIN_GRID_ID970 3.1642730 0.1297337 24.391 < 2e-16 ***
ORIGIN_GRID_ID971 4.4967193 0.1295063 34.722 < 2e-16 ***
ORIGIN_GRID_ID972 4.4397011 0.1295355 34.274 < 2e-16 ***
ORIGIN_GRID_ID974 4.0474690 0.1296815 31.211 < 2e-16 ***
ORIGIN_GRID_ID975 3.7026826 0.1297874 28.529 < 2e-16 ***
ORIGIN_GRID_ID976 2.4440669 0.1306213 18.711 < 2e-16 ***
ORIGIN_GRID_ID977 5.6141277 0.1295011 43.352 < 2e-16 ***
ORIGIN_GRID_ID978 5.5276259 0.1296484 42.636 < 2e-16 ***
ORIGIN_GRID_ID982 2.4261226 0.1305489 18.584 < 2e-16 ***
ORIGIN_GRID_ID983 7.2858423 0.1295155 56.255 < 2e-16 ***
ORIGIN_GRID_ID984 7.6370347 0.1295726 58.940 < 2e-16 ***
ORIGIN_GRID_ID991 3.1439219 0.1298207 24.217 < 2e-16 ***
ORIGIN_GRID_ID992 3.5143167 0.1296498 27.106 < 2e-16 ***
ORIGIN_GRID_ID993 3.2004916 0.1296993 24.676 < 2e-16 ***
ORIGIN_GRID_ID994 2.7531514 0.1299935 21.179 < 2e-16 ***
ORIGIN_GRID_ID995 4.2424401 0.1295811 32.740 < 2e-16 ***
ORIGIN_GRID_ID996 3.9366370 0.1297048 30.351 < 2e-16 ***
ORIGIN_GRID_ID997 2.7003162 0.1328890 20.320 < 2e-16 ***
ORIGIN_GRID_ID998 5.7219817 0.1295061 44.183 < 2e-16 ***
ORIGIN_GRID_ID999 5.7085853 0.1295842 44.053 < 2e-16 ***
ORIGIN_GRID_ID1001 2.6050389 0.1320387 19.729 < 2e-16 ***
ORIGIN_GRID_ID1003 5.2345269 0.1295286 40.412 < 2e-16 ***
ORIGIN_GRID_ID1004 6.0022075 0.1294980 46.350 < 2e-16 ***
ORIGIN_GRID_ID1011 1.3621888 0.1339499 10.169 < 2e-16 ***
ORIGIN_GRID_ID1012 0.9439470 0.1360416 6.939 3.96e-12 ***
ORIGIN_GRID_ID1013 1.8347406 0.1308356 14.023 < 2e-16 ***
ORIGIN_GRID_ID1014 2.7357629 0.1299935 21.045 < 2e-16 ***
ORIGIN_GRID_ID1015 2.0382860 0.1308012 15.583 < 2e-16 ***
ORIGIN_GRID_ID1016 3.8702403 0.1296942 29.841 < 2e-16 ***
ORIGIN_GRID_ID1018 4.6072515 0.1298512 35.481 < 2e-16 ***
ORIGIN_GRID_ID1019 6.1294092 0.1295443 47.315 < 2e-16 ***
ORIGIN_GRID_ID1023 4.2275138 0.1298149 32.566 < 2e-16 ***
ORIGIN_GRID_ID1024 5.2607386 0.1295385 40.611 < 2e-16 ***
ORIGIN_GRID_ID1025 0.4667723 0.1461896 3.193 0.001408 **
ORIGIN_GRID_ID1033 2.4771423 0.1301146 19.038 < 2e-16 ***
ORIGIN_GRID_ID1034 3.4985125 0.1296893 26.976 < 2e-16 ***
ORIGIN_GRID_ID1035 4.2753315 0.1295705 32.996 < 2e-16 ***
ORIGIN_GRID_ID1036 2.0692287 0.1307327 15.828 < 2e-16 ***
ORIGIN_GRID_ID1037 3.4845514 0.1296811 26.870 < 2e-16 ***
ORIGIN_GRID_ID1043 2.5297262 0.1322113 19.134 < 2e-16 ***
ORIGIN_GRID_ID1045 4.9092459 0.1295352 37.899 < 2e-16 ***
ORIGIN_GRID_ID1046 4.8625929 0.1295650 37.530 < 2e-16 ***
ORIGIN_GRID_ID1053 4.0761260 0.1295987 31.452 < 2e-16 ***
ORIGIN_GRID_ID1054 2.9527871 0.1297879 22.751 < 2e-16 ***
ORIGIN_GRID_ID1055 4.1349391 0.1295642 31.914 < 2e-16 ***
ORIGIN_GRID_ID1056 3.1382414 0.1298386 24.170 < 2e-16 ***
ORIGIN_GRID_ID1064 0.2313295 0.2889116 0.801 0.423309
ORIGIN_GRID_ID1066 4.6060612 0.1295634 35.551 < 2e-16 ***
ORIGIN_GRID_ID1067 -0.9412859 0.2417407 -3.894 9.87e-05 ***
ORIGIN_GRID_ID1074 3.3613756 0.1297265 25.911 < 2e-16 ***
ORIGIN_GRID_ID1075 2.5478590 0.1300210 19.596 < 2e-16 ***
ORIGIN_GRID_ID1076 2.8386045 0.1297927 21.870 < 2e-16 ***
ORIGIN_GRID_ID1077 2.9991050 0.1299392 23.081 < 2e-16 ***
ORIGIN_GRID_ID1079 4.4037911 0.1295736 33.987 < 2e-16 ***
ORIGIN_GRID_ID1085 -1.4942062 0.2215643 -6.744 1.54e-11 ***
ORIGIN_GRID_ID1087 4.6117800 0.1295951 35.586 < 2e-16 ***
ORIGIN_GRID_ID1088 2.8910933 0.1300632 22.228 < 2e-16 ***
ORIGIN_GRID_ID1094 1.3886800 0.1386628 10.015 < 2e-16 ***
ORIGIN_GRID_ID1095 0.7895967 0.1368177 5.771 7.87e-09 ***
ORIGIN_GRID_ID1096 2.8250934 0.1314548 21.491 < 2e-16 ***
ORIGIN_GRID_ID1097 4.7965179 0.1295064 37.037 < 2e-16 ***
ORIGIN_GRID_ID1098 2.3983914 0.1309875 18.310 < 2e-16 ***
ORIGIN_GRID_ID1099 3.8189156 0.1296538 29.455 < 2e-16 ***
ORIGIN_GRID_ID1105 1.3177338 0.1520070 8.669 < 2e-16 ***
ORIGIN_GRID_ID1106 -0.2230008 0.1726097 -1.292 0.196379
ORIGIN_GRID_ID1107 2.2010992 0.1330997 16.537 < 2e-16 ***
ORIGIN_GRID_ID1108 6.5363295 0.1294793 50.482 < 2e-16 ***
ORIGIN_GRID_ID1109 1.6638193 0.1324311 12.564 < 2e-16 ***
ORIGIN_GRID_ID1116 3.1767457 0.1297910 24.476 < 2e-16 ***
ORIGIN_GRID_ID1117 1.5070193 0.1314810 11.462 < 2e-16 ***
ORIGIN_GRID_ID1118 2.0002553 0.1311016 15.257 < 2e-16 ***
ORIGIN_GRID_ID1119 2.9854977 0.1299447 22.975 < 2e-16 ***
ORIGIN_GRID_ID1120 2.9516772 0.1302826 22.656 < 2e-16 ***
ORIGIN_GRID_ID1129 4.9220751 0.1295511 37.993 < 2e-16 ***
ORIGIN_GRID_ID1130 4.9717522 0.1295200 38.386 < 2e-16 ***
ORIGIN_GRID_ID1131 2.9342823 0.1305692 22.473 < 2e-16 ***
ORIGIN_GRID_ID1136 2.2170077 0.1304007 17.001 < 2e-16 ***
ORIGIN_GRID_ID1138 1.0184739 0.1357085 7.505 6.15e-14 ***
ORIGIN_GRID_ID1139 3.9709996 0.1295689 30.648 < 2e-16 ***
ORIGIN_GRID_ID1141 3.9431499 0.1296240 30.420 < 2e-16 ***
ORIGIN_GRID_ID1148 1.4981269 0.1388340 10.791 < 2e-16 ***
ORIGIN_GRID_ID1149 2.6959302 0.1310126 20.578 < 2e-16 ***
ORIGIN_GRID_ID1150 5.1991862 0.1295098 40.145 < 2e-16 ***
ORIGIN_GRID_ID1151 4.0733174 0.1296334 31.422 < 2e-16 ***
ORIGIN_GRID_ID1158 2.2617634 0.1300706 17.389 < 2e-16 ***
ORIGIN_GRID_ID1159 3.7517807 0.1295930 28.950 < 2e-16 ***
ORIGIN_GRID_ID1160 4.7957315 0.1295089 37.030 < 2e-16 ***
ORIGIN_GRID_ID1171 5.7759513 0.1295208 44.595 < 2e-16 ***
ORIGIN_GRID_ID1172 5.5831383 0.1295181 43.107 < 2e-16 ***
ORIGIN_GRID_ID1173 2.8695849 0.1301764 22.044 < 2e-16 ***
ORIGIN_GRID_ID1174 -1.3592719 0.2888991 -4.705 2.54e-06 ***
ORIGIN_GRID_ID1178 2.5015752 0.1300000 19.243 < 2e-16 ***
ORIGIN_GRID_ID1179 3.1744589 0.1296875 24.478 < 2e-16 ***
ORIGIN_GRID_ID1180 4.2756242 0.1295333 33.008 < 2e-16 ***
ORIGIN_GRID_ID1181 3.5621437 0.1296505 27.475 < 2e-16 ***
ORIGIN_GRID_ID1183 2.6609130 0.1302553 20.428 < 2e-16 ***
ORIGIN_GRID_ID1190 1.5872316 0.1390732 11.413 < 2e-16 ***
ORIGIN_GRID_ID1192 4.4637181 0.1296299 34.434 < 2e-16 ***
ORIGIN_GRID_ID1193 4.4458141 0.1295774 34.310 < 2e-16 ***
ORIGIN_GRID_ID1194 2.6667882 0.1304031 20.450 < 2e-16 ***
ORIGIN_GRID_ID1200 3.3420886 0.1296576 25.776 < 2e-16 ***
ORIGIN_GRID_ID1201 3.1206538 0.1296973 24.061 < 2e-16 ***
ORIGIN_GRID_ID1203 4.0313110 0.1296076 31.104 < 2e-16 ***
ORIGIN_GRID_ID1204 3.8794258 0.1296304 29.927 < 2e-16 ***
ORIGIN_GRID_ID1211 0.3767496 0.2538829 1.484 0.137822
ORIGIN_GRID_ID1214 5.2596277 0.1295276 40.606 < 2e-16 ***
ORIGIN_GRID_ID1215 1.6359589 0.1368581 11.954 < 2e-16 ***
ORIGIN_GRID_ID1216 0.7661547 0.1365196 5.612 2.00e-08 ***
ORIGIN_GRID_ID1220 4.2950521 0.1295318 33.158 < 2e-16 ***
ORIGIN_GRID_ID1221 3.9885297 0.1295449 30.789 < 2e-16 ***
ORIGIN_GRID_ID1222 3.6511656 0.1298980 28.108 < 2e-16 ***
ORIGIN_GRID_ID1223 1.9409617 0.1308655 14.832 < 2e-16 ***
ORIGIN_GRID_ID1224 2.8147645 0.1299928 21.653 < 2e-16 ***
ORIGIN_GRID_ID1231 -1.1229725 0.2382831 -4.713 2.44e-06 ***
ORIGIN_GRID_ID1232 1.5084913 0.1571621 9.598 < 2e-16 ***
ORIGIN_GRID_ID1235 2.7645251 0.1302555 21.224 < 2e-16 ***
ORIGIN_GRID_ID1236 2.5426870 0.1303673 19.504 < 2e-16 ***
ORIGIN_GRID_ID1241 2.5176658 0.1299736 19.371 < 2e-16 ***
ORIGIN_GRID_ID1242 3.1909520 0.1296660 24.609 < 2e-16 ***
ORIGIN_GRID_ID1243 3.8013067 0.1295643 29.339 < 2e-16 ***
ORIGIN_GRID_ID1246 2.9961166 0.1298684 23.070 < 2e-16 ***
ORIGIN_GRID_ID1256 4.2209013 0.1296836 32.548 < 2e-16 ***
ORIGIN_GRID_ID1257 5.1124974 0.1295794 39.455 < 2e-16 ***
ORIGIN_GRID_ID1258 3.0598355 0.1303269 23.478 < 2e-16 ***
ORIGIN_GRID_ID1262 2.9618378 0.1297723 22.823 < 2e-16 ***
ORIGIN_GRID_ID1263 3.3987079 0.1295950 26.226 < 2e-16 ***
ORIGIN_GRID_ID1264 2.3822735 0.1302348 18.292 < 2e-16 ***
ORIGIN_GRID_ID1265 2.0603736 0.1307142 15.762 < 2e-16 ***
ORIGIN_GRID_ID1266 3.7007552 0.1297084 28.531 < 2e-16 ***
ORIGIN_GRID_ID1267 1.5897728 0.1336323 11.897 < 2e-16 ***
ORIGIN_GRID_ID1272 -0.8208383 0.1962384 -4.183 2.88e-05 ***
ORIGIN_GRID_ID1273 3.5180052 0.1301366 27.033 < 2e-16 ***
ORIGIN_GRID_ID1277 5.1748134 0.1295299 39.951 < 2e-16 ***
ORIGIN_GRID_ID1278 2.5545537 0.1303166 19.603 < 2e-16 ***
ORIGIN_GRID_ID1283 4.6711268 0.1295217 36.064 < 2e-16 ***
ORIGIN_GRID_ID1284 3.9411748 0.1295578 30.420 < 2e-16 ***
ORIGIN_GRID_ID1285 4.5727893 0.1295054 35.310 < 2e-16 ***
ORIGIN_GRID_ID1286 2.7600581 0.1300137 21.229 < 2e-16 ***
ORIGIN_GRID_ID1289 1.1192065 0.1403944 7.972 1.56e-15 ***
ORIGIN_GRID_ID1293 0.2433618 0.1533844 1.587 0.112600
ORIGIN_GRID_ID1294 5.0161402 0.1296160 38.700 < 2e-16 ***
ORIGIN_GRID_ID1295 2.4502333 0.1314309 18.643 < 2e-16 ***
ORIGIN_GRID_ID1298 4.2519153 0.1296536 32.794 < 2e-16 ***
ORIGIN_GRID_ID1299 4.6170553 0.1296170 35.621 < 2e-16 ***
ORIGIN_GRID_ID1304 4.5763567 0.1295203 35.333 < 2e-16 ***
ORIGIN_GRID_ID1305 3.9349022 0.1295315 30.378 < 2e-16 ***
ORIGIN_GRID_ID1307 0.1549684 0.1400384 1.107 0.268461
ORIGIN_GRID_ID1308 3.7597806 0.1296338 29.003 < 2e-16 ***
ORIGIN_GRID_ID1310 -1.0825770 0.2689192 -4.026 5.68e-05 ***
ORIGIN_GRID_ID1316 1.5498682 0.1344863 11.524 < 2e-16 ***
ORIGIN_GRID_ID1317 3.2295363 0.1300192 24.839 < 2e-16 ***
ORIGIN_GRID_ID1318 2.5227906 0.1305432 19.325 < 2e-16 ***
ORIGIN_GRID_ID1319 5.4871546 0.1295216 42.365 < 2e-16 ***
ORIGIN_GRID_ID1320 4.0379363 0.1297846 31.113 < 2e-16 ***
ORIGIN_GRID_ID1325 2.1789374 0.1301675 16.739 < 2e-16 ***
ORIGIN_GRID_ID1326 4.1432950 0.1295269 31.988 < 2e-16 ***
ORIGIN_GRID_ID1327 3.8787318 0.1295514 29.940 < 2e-16 ***
ORIGIN_GRID_ID1328 2.4971168 0.1299301 19.219 < 2e-16 ***
ORIGIN_GRID_ID1329 2.7918519 0.1301149 21.457 < 2e-16 ***
ORIGIN_GRID_ID1330 3.6792124 0.1297656 28.353 < 2e-16 ***
ORIGIN_GRID_ID1331 -1.3192443 0.3576114 -3.689 0.000225 ***
ORIGIN_GRID_ID1333 3.0796911 0.1301369 23.665 < 2e-16 ***
ORIGIN_GRID_ID1334 3.3346033 0.1300422 25.642 < 2e-16 ***
ORIGIN_GRID_ID1335 2.9346059 0.1307106 22.451 < 2e-16 ***
ORIGIN_GRID_ID1336 0.1070655 0.1897186 0.564 0.572524
ORIGIN_GRID_ID1337 0.4999919 0.1417573 3.527 0.000420 ***
ORIGIN_GRID_ID1338 -0.8942589 0.1724814 -5.185 2.16e-07 ***
ORIGIN_GRID_ID1339 5.3258581 0.1295176 41.121 < 2e-16 ***
ORIGIN_GRID_ID1340 3.7443747 0.1297874 28.850 < 2e-16 ***
ORIGIN_GRID_ID1341 0.8444983 0.2584338 3.268 0.001084 **
ORIGIN_GRID_ID1346 3.7631360 0.1296375 29.028 < 2e-16 ***
ORIGIN_GRID_ID1347 4.7620895 0.1295069 36.771 < 2e-16 ***
ORIGIN_GRID_ID1348 3.1107620 0.1296550 23.993 < 2e-16 ***
ORIGIN_GRID_ID1349 2.9350237 0.1298055 22.611 < 2e-16 ***
ORIGIN_GRID_ID1350 3.2858980 0.1299912 25.278 < 2e-16 ***
ORIGIN_GRID_ID1353 3.0854613 0.1298986 23.753 < 2e-16 ***
ORIGIN_GRID_ID1354 2.8453012 0.1301870 21.855 < 2e-16 ***
ORIGIN_GRID_ID1355 3.6657993 0.1297738 28.248 < 2e-16 ***
ORIGIN_GRID_ID1357 2.6871868 0.1310859 20.499 < 2e-16 ***
ORIGIN_GRID_ID1358 4.0924742 0.1296872 31.556 < 2e-16 ***
ORIGIN_GRID_ID1359 4.3740010 0.1295758 33.756 < 2e-16 ***
ORIGIN_GRID_ID1360 4.5002285 0.1295775 34.730 < 2e-16 ***
ORIGIN_GRID_ID1361 5.5974930 0.1295300 43.214 < 2e-16 ***
ORIGIN_GRID_ID1362 1.7086920 0.1359624 12.567 < 2e-16 ***
ORIGIN_GRID_ID1368 2.6286759 0.1298059 20.251 < 2e-16 ***
ORIGIN_GRID_ID1369 2.3347830 0.1298682 17.978 < 2e-16 ***
ORIGIN_GRID_ID1370 3.5689889 0.1295748 27.544 < 2e-16 ***
ORIGIN_GRID_ID1371 2.9541775 0.1299329 22.736 < 2e-16 ***
ORIGIN_GRID_ID1372 2.2670563 0.1301972 17.412 < 2e-16 ***
ORIGIN_GRID_ID1373 0.6496382 0.1397512 4.649 3.34e-06 ***
ORIGIN_GRID_ID1374 2.5739084 0.1300929 19.785 < 2e-16 ***
ORIGIN_GRID_ID1375 4.1129784 0.1297222 31.706 < 2e-16 ***
ORIGIN_GRID_ID1376 3.4041269 0.1301996 26.145 < 2e-16 ***
ORIGIN_GRID_ID1379 1.7169568 0.1344531 12.770 < 2e-16 ***
ORIGIN_GRID_ID1380 5.7188048 0.1294947 44.162 < 2e-16 ***
ORIGIN_GRID_ID1381 5.3070919 0.1295171 40.976 < 2e-16 ***
ORIGIN_GRID_ID1382 4.8010838 0.1296224 37.039 < 2e-16 ***
ORIGIN_GRID_ID1383 2.4105667 0.1320031 18.261 < 2e-16 ***
ORIGIN_GRID_ID1388 3.1647932 0.1296679 24.407 < 2e-16 ***
ORIGIN_GRID_ID1389 1.9076729 0.1300750 14.666 < 2e-16 ***
ORIGIN_GRID_ID1390 3.0545389 0.1296826 23.554 < 2e-16 ***
ORIGIN_GRID_ID1391 3.1440758 0.1297334 24.235 < 2e-16 ***
ORIGIN_GRID_ID1392 2.6483165 0.1308362 20.241 < 2e-16 ***
ORIGIN_GRID_ID1393 1.8181323 0.1304832 13.934 < 2e-16 ***
ORIGIN_GRID_ID1394 3.2705018 0.1297144 25.213 < 2e-16 ***
ORIGIN_GRID_ID1395 3.3471726 0.1297126 25.805 < 2e-16 ***
ORIGIN_GRID_ID1396 4.4581238 0.1295633 34.409 < 2e-16 ***
ORIGIN_GRID_ID1397 4.5332998 0.1295722 34.987 < 2e-16 ***
ORIGIN_GRID_ID1398 3.4666942 0.1299893 26.669 < 2e-16 ***
ORIGIN_GRID_ID1400 4.6362913 0.1296314 35.765 < 2e-16 ***
ORIGIN_GRID_ID1401 5.7504696 0.1294892 44.409 < 2e-16 ***
ORIGIN_GRID_ID1402 4.9750631 0.1295383 38.406 < 2e-16 ***
ORIGIN_GRID_ID1404 5.0850101 0.1304504 38.980 < 2e-16 ***
ORIGIN_GRID_ID1410 2.6793412 0.1297422 20.651 < 2e-16 ***
ORIGIN_GRID_ID1411 2.7217848 0.1297641 20.975 < 2e-16 ***
ORIGIN_GRID_ID1412 2.9893343 0.1296547 23.056 < 2e-16 ***
ORIGIN_GRID_ID1413 3.8827367 0.1295706 29.966 < 2e-16 ***
ORIGIN_GRID_ID1414 3.2568073 0.1296383 25.122 < 2e-16 ***
ORIGIN_GRID_ID1415 2.8016999 0.1298485 21.577 < 2e-16 ***
ORIGIN_GRID_ID1416 3.4780751 0.1296640 26.824 < 2e-16 ***
ORIGIN_GRID_ID1417 3.6156930 0.1296461 27.889 < 2e-16 ***
ORIGIN_GRID_ID1418 4.4301719 0.1295543 34.195 < 2e-16 ***
ORIGIN_GRID_ID1419 3.9006276 0.1296472 30.086 < 2e-16 ***
ORIGIN_GRID_ID1422 5.1652886 0.1295466 39.872 < 2e-16 ***
ORIGIN_GRID_ID1423 5.9025080 0.1295061 45.577 < 2e-16 ***
ORIGIN_GRID_ID1430 3.4767218 0.1296258 26.821 < 2e-16 ***
ORIGIN_GRID_ID1431 3.4462093 0.1295756 26.596 < 2e-16 ***
ORIGIN_GRID_ID1432 3.5722668 0.1295648 27.571 < 2e-16 ***
ORIGIN_GRID_ID1433 2.3160751 0.1307329 17.716 < 2e-16 ***
ORIGIN_GRID_ID1434 3.8508584 0.1295847 29.717 < 2e-16 ***
ORIGIN_GRID_ID1435 4.2533334 0.1295219 32.839 < 2e-16 ***
ORIGIN_GRID_ID1436 1.1200426 0.1320557 8.482 < 2e-16 ***
ORIGIN_GRID_ID1437 4.4296078 0.1295366 34.196 < 2e-16 ***
ORIGIN_GRID_ID1438 4.9184866 0.1294992 37.981 < 2e-16 ***
ORIGIN_GRID_ID1439 5.5130796 0.1294896 42.575 < 2e-16 ***
ORIGIN_GRID_ID1440 1.9597446 0.1312150 14.935 < 2e-16 ***
ORIGIN_GRID_ID1442 4.8890638 0.1296304 37.715 < 2e-16 ***
ORIGIN_GRID_ID1443 5.8506395 0.1295126 45.174 < 2e-16 ***
ORIGIN_GRID_ID1444 4.9013684 0.1296970 37.791 < 2e-16 ***
ORIGIN_GRID_ID1452 2.5590745 0.1297795 19.719 < 2e-16 ***
ORIGIN_GRID_ID1453 2.6929401 0.1297513 20.755 < 2e-16 ***
ORIGIN_GRID_ID1454 1.7979696 0.1311476 13.710 < 2e-16 ***
ORIGIN_GRID_ID1455 3.2131044 0.1297748 24.759 < 2e-16 ***
ORIGIN_GRID_ID1456 3.6186115 0.1296137 27.918 < 2e-16 ***
ORIGIN_GRID_ID1457 4.4874811 0.1295233 34.646 < 2e-16 ***
ORIGIN_GRID_ID1458 4.8234700 0.1295081 37.245 < 2e-16 ***
ORIGIN_GRID_ID1459 4.2646529 0.1295438 32.921 < 2e-16 ***
ORIGIN_GRID_ID1460 3.4551478 0.1296409 26.652 < 2e-16 ***
ORIGIN_GRID_ID1461 2.1064753 0.1307000 16.117 < 2e-16 ***
ORIGIN_GRID_ID1464 6.3318248 0.1295029 48.893 < 2e-16 ***
ORIGIN_GRID_ID1465 5.8445398 0.1295409 45.117 < 2e-16 ***
ORIGIN_GRID_ID1472 1.1281794 0.1315622 8.575 < 2e-16 ***
ORIGIN_GRID_ID1473 2.0928800 0.1299805 16.101 < 2e-16 ***
ORIGIN_GRID_ID1474 3.2644195 0.1295939 25.190 < 2e-16 ***
ORIGIN_GRID_ID1475 4.2386759 0.1295331 32.723 < 2e-16 ***
ORIGIN_GRID_ID1476 3.5850511 0.1296334 27.655 < 2e-16 ***
ORIGIN_GRID_ID1477 5.1354279 0.1294824 39.661 < 2e-16 ***
ORIGIN_GRID_ID1478 3.4520924 0.1296343 26.629 < 2e-16 ***
ORIGIN_GRID_ID1479 3.6804598 0.1295969 28.399 < 2e-16 ***
ORIGIN_GRID_ID1480 5.5028953 0.1294808 42.500 < 2e-16 ***
ORIGIN_GRID_ID1481 2.8408399 0.1298936 21.871 < 2e-16 ***
ORIGIN_GRID_ID1482 3.0567862 0.1302180 23.474 < 2e-16 ***
ORIGIN_GRID_ID1485 5.8064007 0.1295453 44.821 < 2e-16 ***
ORIGIN_GRID_ID1494 2.3291143 0.1302471 17.882 < 2e-16 ***
ORIGIN_GRID_ID1495 2.5715454 0.1297673 19.817 < 2e-16 ***
ORIGIN_GRID_ID1496 3.7158851 0.1295497 28.683 < 2e-16 ***
ORIGIN_GRID_ID1497 4.0640432 0.1295668 31.366 < 2e-16 ***
ORIGIN_GRID_ID1498 4.4226607 0.1295210 34.146 < 2e-16 ***
ORIGIN_GRID_ID1499 4.6614904 0.1295058 35.994 < 2e-16 ***
ORIGIN_GRID_ID1500 4.5611477 0.1295740 35.201 < 2e-16 ***
ORIGIN_GRID_ID1501 4.7996179 0.1295073 37.061 < 2e-16 ***
ORIGIN_GRID_ID1502 4.2454286 0.1295476 32.771 < 2e-16 ***
ORIGIN_GRID_ID1506 0.3806353 0.1685016 2.259 0.023887 *
ORIGIN_GRID_ID1515 1.5045978 0.1320470 11.394 < 2e-16 ***
ORIGIN_GRID_ID1516 2.9584912 0.1296911 22.812 < 2e-16 ***
ORIGIN_GRID_ID1517 3.4439597 0.1296567 26.562 < 2e-16 ***
ORIGIN_GRID_ID1518 3.3449247 0.1296891 25.792 < 2e-16 ***
ORIGIN_GRID_ID1519 4.6948232 0.1295531 36.239 < 2e-16 ***
ORIGIN_GRID_ID1520 3.3950764 0.1296534 26.186 < 2e-16 ***
ORIGIN_GRID_ID1521 2.7364277 0.1299278 21.061 < 2e-16 ***
ORIGIN_GRID_ID1522 5.0054001 0.1295000 38.652 < 2e-16 ***
ORIGIN_GRID_ID1523 3.4962562 0.1304742 26.797 < 2e-16 ***
ORIGIN_GRID_ID1524 3.6681333 0.1298432 28.250 < 2e-16 ***
ORIGIN_GRID_ID1527 3.6646477 0.1304970 28.082 < 2e-16 ***
ORIGIN_GRID_ID1535 -0.0222476 0.1641485 -0.136 0.892190
ORIGIN_GRID_ID1536 0.8566993 0.1342057 6.383 1.73e-10 ***
ORIGIN_GRID_ID1537 1.5539459 0.1310465 11.858 < 2e-16 ***
ORIGIN_GRID_ID1538 3.1872940 0.1296315 24.587 < 2e-16 ***
ORIGIN_GRID_ID1539 3.7224570 0.1295638 28.731 < 2e-16 ***
ORIGIN_GRID_ID1540 4.3175125 0.1295271 33.333 < 2e-16 ***
ORIGIN_GRID_ID1541 5.5109438 0.1295712 42.532 < 2e-16 ***
ORIGIN_GRID_ID1542 2.4570294 0.1304566 18.834 < 2e-16 ***
ORIGIN_GRID_ID1543 3.2839621 0.1314469 24.983 < 2e-16 ***
ORIGIN_GRID_ID1544 4.2543501 0.1296287 32.819 < 2e-16 ***
ORIGIN_GRID_ID1547 1.4569510 0.1427398 10.207 < 2e-16 ***
ORIGIN_GRID_ID1556 1.1187933 0.1488313 7.517 5.60e-14 ***
ORIGIN_GRID_ID1557 0.8693329 0.1347952 6.449 1.12e-10 ***
ORIGIN_GRID_ID1558 2.1097682 0.1311087 16.092 < 2e-16 ***
ORIGIN_GRID_ID1559 3.8467860 0.1295511 29.693 < 2e-16 ***
ORIGIN_GRID_ID1560 4.6938457 0.1295037 36.245 < 2e-16 ***
ORIGIN_GRID_ID1561 4.5596528 0.1295354 35.200 < 2e-16 ***
ORIGIN_GRID_ID1562 1.6215013 0.1312284 12.356 < 2e-16 ***
ORIGIN_GRID_ID1563 3.4379636 0.1296735 26.512 < 2e-16 ***
ORIGIN_GRID_ID1564 2.5975078 0.1302155 19.948 < 2e-16 ***
ORIGIN_GRID_ID1565 2.6590881 0.1302626 20.413 < 2e-16 ***
ORIGIN_GRID_ID1566 2.4087742 0.1310916 18.375 < 2e-16 ***
ORIGIN_GRID_ID1567 0.3332421 0.1605559 2.076 0.037935 *
ORIGIN_GRID_ID1568 1.2461417 0.1460792 8.531 < 2e-16 ***
ORIGIN_GRID_ID1578 -1.5780755 0.2899354 -5.443 5.24e-08 ***
ORIGIN_GRID_ID1580 2.3203641 0.1306488 17.760 < 2e-16 ***
ORIGIN_GRID_ID1581 1.1584719 0.1312989 8.823 < 2e-16 ***
ORIGIN_GRID_ID1582 4.3839866 0.1295112 33.850 < 2e-16 ***
ORIGIN_GRID_ID1583 2.6470767 0.1312375 20.170 < 2e-16 ***
ORIGIN_GRID_ID1584 2.9210781 0.1299130 22.485 < 2e-16 ***
ORIGIN_GRID_ID1585 3.5480803 0.1298291 27.329 < 2e-16 ***
ORIGIN_GRID_ID1586 2.5381139 0.1301953 19.495 < 2e-16 ***
ORIGIN_GRID_ID1589 0.4098652 0.1608097 2.549 0.010811 *
ORIGIN_GRID_ID1590 1.2094477 0.1447444 8.356 < 2e-16 ***
ORIGIN_GRID_ID1600 4.4372327 0.1299013 34.159 < 2e-16 ***
ORIGIN_GRID_ID1601 2.9819181 0.1296979 22.991 < 2e-16 ***
ORIGIN_GRID_ID1602 3.6624927 0.1296064 28.259 < 2e-16 ***
ORIGIN_GRID_ID1603 4.5718702 0.1295151 35.300 < 2e-16 ***
ORIGIN_GRID_ID1604 3.0892076 0.1297151 23.815 < 2e-16 ***
ORIGIN_GRID_ID1605 4.4991251 0.1295230 34.736 < 2e-16 ***
ORIGIN_GRID_ID1606 3.9739802 0.1298331 30.608 < 2e-16 ***
ORIGIN_GRID_ID1607 3.2983029 0.1298181 25.407 < 2e-16 ***
ORIGIN_GRID_ID1608 5.3067054 0.1295304 40.969 < 2e-16 ***
ORIGIN_GRID_ID1609 5.1757552 0.1295799 39.943 < 2e-16 ***
ORIGIN_GRID_ID1610 1.7842327 0.1457141 12.245 < 2e-16 ***
ORIGIN_GRID_ID1622 3.0456760 0.1314447 23.171 < 2e-16 ***
ORIGIN_GRID_ID1623 4.3643410 0.1295171 33.697 < 2e-16 ***
ORIGIN_GRID_ID1624 3.1380008 0.1297305 24.189 < 2e-16 ***
ORIGIN_GRID_ID1625 4.5317251 0.1295373 34.984 < 2e-16 ***
ORIGIN_GRID_ID1626 5.2038954 0.1294933 40.187 < 2e-16 ***
ORIGIN_GRID_ID1627 3.5915647 0.1296629 27.699 < 2e-16 ***
ORIGIN_GRID_ID1628 5.3348031 0.1294962 41.197 < 2e-16 ***
ORIGIN_GRID_ID1629 4.3399782 0.1296337 33.479 < 2e-16 ***
ORIGIN_GRID_ID1630 4.4768038 0.1296872 34.520 < 2e-16 ***
ORIGIN_GRID_ID1631 0.7784235 0.1472007 5.288 1.24e-07 ***
ORIGIN_GRID_ID1642 1.8568067 0.1330323 13.958 < 2e-16 ***
ORIGIN_GRID_ID1643 4.3217561 0.1295280 33.365 < 2e-16 ***
ORIGIN_GRID_ID1644 2.1004495 0.1305989 16.083 < 2e-16 ***
ORIGIN_GRID_ID1645 3.5650904 0.1296057 27.507 < 2e-16 ***
ORIGIN_GRID_ID1646 3.4058926 0.1297880 26.242 < 2e-16 ***
ORIGIN_GRID_ID1647 3.7853800 0.1295901 29.210 < 2e-16 ***
ORIGIN_GRID_ID1648 4.4334305 0.1295429 34.224 < 2e-16 ***
ORIGIN_GRID_ID1649 5.2145607 0.1295032 40.266 < 2e-16 ***
ORIGIN_GRID_ID1650 5.3302350 0.1295634 41.140 < 2e-16 ***
ORIGIN_GRID_ID1664 -0.7733142 0.1962788 -3.940 8.15e-05 ***
ORIGIN_GRID_ID1665 4.4962153 0.1295130 34.716 < 2e-16 ***
ORIGIN_GRID_ID1666 3.1840792 0.1296627 24.557 < 2e-16 ***
ORIGIN_GRID_ID1667 4.1844781 0.1299080 32.211 < 2e-16 ***
ORIGIN_GRID_ID1668 4.3364071 0.1295391 33.476 < 2e-16 ***
ORIGIN_GRID_ID1670 5.2317954 0.1294963 40.401 < 2e-16 ***
ORIGIN_GRID_ID1671 5.9524395 0.1295589 45.944 < 2e-16 ***
ORIGIN_GRID_ID1672 5.6252874 0.1295851 43.410 < 2e-16 ***
ORIGIN_GRID_ID1684 3.4636065 0.1301729 26.608 < 2e-16 ***
ORIGIN_GRID_ID1685 4.0641380 0.1295662 31.367 < 2e-16 ***
ORIGIN_GRID_ID1686 3.9228167 0.1295698 30.276 < 2e-16 ***
ORIGIN_GRID_ID1687 3.5059540 0.1296817 27.035 < 2e-16 ***
ORIGIN_GRID_ID1688 3.0426975 0.1297594 23.449 < 2e-16 ***
ORIGIN_GRID_ID1689 2.6432585 0.1301515 20.309 < 2e-16 ***
ORIGIN_GRID_ID1690 4.1599227 0.1296239 32.092 < 2e-16 ***
ORIGIN_GRID_ID1691 4.9485637 0.1295280 38.205 < 2e-16 ***
ORIGIN_GRID_ID1692 4.5393137 0.1297243 34.992 < 2e-16 ***
ORIGIN_GRID_ID1706 3.9987074 0.1296198 30.850 < 2e-16 ***
ORIGIN_GRID_ID1707 3.9528381 0.1295536 30.511 < 2e-16 ***
ORIGIN_GRID_ID1708 4.4573662 0.1295175 34.415 < 2e-16 ***
ORIGIN_GRID_ID1709 3.6057918 0.1296273 27.817 < 2e-16 ***
ORIGIN_GRID_ID1710 4.7791790 0.1295213 36.899 < 2e-16 ***
ORIGIN_GRID_ID1711 4.5230963 0.1295588 34.912 < 2e-16 ***
ORIGIN_GRID_ID1712 5.2083293 0.1294969 40.220 < 2e-16 ***
ORIGIN_GRID_ID1713 2.8339232 0.1301624 21.772 < 2e-16 ***
ORIGIN_GRID_ID1714 5.5128791 0.1295404 42.557 < 2e-16 ***
ORIGIN_GRID_ID1727 4.2571514 0.1295658 32.857 < 2e-16 ***
ORIGIN_GRID_ID1728 4.0688392 0.1295502 31.407 < 2e-16 ***
ORIGIN_GRID_ID1729 3.5347017 0.1295918 27.276 < 2e-16 ***
ORIGIN_GRID_ID1730 1.5773195 0.1315246 11.993 < 2e-16 ***
ORIGIN_GRID_ID1731 4.3765339 0.1295583 33.780 < 2e-16 ***
ORIGIN_GRID_ID1732 4.8940058 0.1295068 37.790 < 2e-16 ***
ORIGIN_GRID_ID1733 4.6939312 0.1295322 36.238 < 2e-16 ***
ORIGIN_GRID_ID1734 5.1231881 0.1295256 39.553 < 2e-16 ***
ORIGIN_GRID_ID1735 6.8581899 0.1296258 52.908 < 2e-16 ***
ORIGIN_GRID_ID1748 2.9256947 0.1298780 22.526 < 2e-16 ***
ORIGIN_GRID_ID1749 3.8938524 0.1295607 30.054 < 2e-16 ***
ORIGIN_GRID_ID1750 3.0459731 0.1296911 23.486 < 2e-16 ***
ORIGIN_GRID_ID1751 2.4362025 0.1299451 18.748 < 2e-16 ***
ORIGIN_GRID_ID1753 4.9607305 0.1295111 38.304 < 2e-16 ***
ORIGIN_GRID_ID1754 5.3192322 0.1294944 41.077 < 2e-16 ***
ORIGIN_GRID_ID1755 4.8776320 0.1295282 37.657 < 2e-16 ***
ORIGIN_GRID_ID1756 4.8259240 0.1295695 37.246 < 2e-16 ***
ORIGIN_GRID_ID1757 2.8364544 0.1338285 21.195 < 2e-16 ***
ORIGIN_GRID_ID1769 3.7745086 0.1296066 29.123 < 2e-16 ***
ORIGIN_GRID_ID1770 3.3692827 0.1298936 25.939 < 2e-16 ***
ORIGIN_GRID_ID1771 2.5007830 0.1299662 19.242 < 2e-16 ***
ORIGIN_GRID_ID1772 1.2843165 0.1322683 9.710 < 2e-16 ***
ORIGIN_GRID_ID1774 4.6718031 0.1295260 36.068 < 2e-16 ***
ORIGIN_GRID_ID1775 4.3423116 0.1295770 33.511 < 2e-16 ***
ORIGIN_GRID_ID1776 5.5263671 0.1294983 42.675 < 2e-16 ***
ORIGIN_GRID_ID1777 5.6095188 0.1295138 43.312 < 2e-16 ***
ORIGIN_GRID_ID1778 5.4076927 0.1300674 41.576 < 2e-16 ***
ORIGIN_GRID_ID1790 4.4364134 0.1295559 34.243 < 2e-16 ***
ORIGIN_GRID_ID1791 3.7798805 0.1296324 29.158 < 2e-16 ***
ORIGIN_GRID_ID1792 3.7745048 0.1296493 29.113 < 2e-16 ***
ORIGIN_GRID_ID1793 1.6172047 0.1304216 12.400 < 2e-16 ***
ORIGIN_GRID_ID1794 1.5787421 0.1326497 11.902 < 2e-16 ***
ORIGIN_GRID_ID1795 1.1586645 0.1339558 8.650 < 2e-16 ***
ORIGIN_GRID_ID1796 5.1877694 0.1295271 40.052 < 2e-16 ***
ORIGIN_GRID_ID1797 5.1910037 0.1295129 40.081 < 2e-16 ***
ORIGIN_GRID_ID1798 5.2439461 0.1295136 40.490 < 2e-16 ***
ORIGIN_GRID_ID1799 4.5035976 0.1296875 34.727 < 2e-16 ***
ORIGIN_GRID_ID1800 3.8376760 0.1324762 28.969 < 2e-16 ***
ORIGIN_GRID_ID1811 3.5285186 0.1296903 27.207 < 2e-16 ***
ORIGIN_GRID_ID1812 4.6774563 0.1295049 36.118 < 2e-16 ***
ORIGIN_GRID_ID1813 4.4769708 0.1295146 34.567 < 2e-16 ***
ORIGIN_GRID_ID1817 5.0892593 0.1295664 39.279 < 2e-16 ***
ORIGIN_GRID_ID1818 5.0386588 0.1295340 38.898 < 2e-16 ***
ORIGIN_GRID_ID1819 5.5507526 0.1295074 42.860 < 2e-16 ***
ORIGIN_GRID_ID1820 2.7655818 0.1346203 20.544 < 2e-16 ***
ORIGIN_GRID_ID1832 4.2123057 0.1295798 32.507 < 2e-16 ***
ORIGIN_GRID_ID1833 3.7591680 0.1296044 29.005 < 2e-16 ***
ORIGIN_GRID_ID1834 4.1064346 0.1295373 31.701 < 2e-16 ***
ORIGIN_GRID_ID1835 3.3930733 0.1296853 26.164 < 2e-16 ***
ORIGIN_GRID_ID1837 0.6406136 0.1440776 4.446 8.74e-06 ***
ORIGIN_GRID_ID1839 4.5075602 0.1296669 34.763 < 2e-16 ***
ORIGIN_GRID_ID1840 6.3004700 0.1294825 48.659 < 2e-16 ***
ORIGIN_GRID_ID1841 1.8086252 0.1374016 13.163 < 2e-16 ***
ORIGIN_GRID_ID1842 6.2708955 0.1299713 48.248 < 2e-16 ***
ORIGIN_GRID_ID1853 4.1726198 0.1295545 32.207 < 2e-16 ***
ORIGIN_GRID_ID1854 4.3667509 0.1295446 33.708 < 2e-16 ***
ORIGIN_GRID_ID1855 4.6758606 0.1295232 36.101 < 2e-16 ***
ORIGIN_GRID_ID1858 2.4597156 0.1322742 18.596 < 2e-16 ***
ORIGIN_GRID_ID1860 5.8323722 0.1297607 44.947 < 2e-16 ***
ORIGIN_GRID_ID1861 5.2984290 0.1295389 40.902 < 2e-16 ***
ORIGIN_GRID_ID1874 4.3262165 0.1296126 33.378 < 2e-16 ***
ORIGIN_GRID_ID1875 2.6848247 0.1301848 20.623 < 2e-16 ***
ORIGIN_GRID_ID1876 4.7487062 0.1299313 36.548 < 2e-16 ***
ORIGIN_GRID_ID1877 4.3945499 0.1295464 33.923 < 2e-16 ***
ORIGIN_GRID_ID1880 0.8356641 0.1385159 6.033 1.61e-09 ***
ORIGIN_GRID_ID1882 5.1394705 0.1295514 39.671 < 2e-16 ***
ORIGIN_GRID_ID1883 5.6486566 0.1297880 43.522 < 2e-16 ***
ORIGIN_GRID_ID1895 4.4595812 0.1295461 34.425 < 2e-16 ***
ORIGIN_GRID_ID1896 2.8399662 0.1298450 21.872 < 2e-16 ***
ORIGIN_GRID_ID1897 3.4723325 0.1297957 26.752 < 2e-16 ***
ORIGIN_GRID_ID1898 -0.9082304 0.1987272 -4.570 4.87e-06 ***
ORIGIN_GRID_ID1901 0.7063593 0.1483586 4.761 1.92e-06 ***
ORIGIN_GRID_ID1903 5.0491019 0.1297745 38.907 < 2e-16 ***
ORIGIN_GRID_ID1917 2.9822210 0.1298458 22.967 < 2e-16 ***
ORIGIN_GRID_ID1918 4.5009882 0.1295946 34.731 < 2e-16 ***
ORIGIN_GRID_ID1919 4.3632105 0.1295637 33.676 < 2e-16 ***
ORIGIN_GRID_ID1922 2.2066815 0.1325037 16.654 < 2e-16 ***
ORIGIN_GRID_ID1924 4.8607624 0.1298154 37.444 < 2e-16 ***
ORIGIN_GRID_ID1937 3.8096978 0.1296567 29.383 < 2e-16 ***
ORIGIN_GRID_ID1938 4.5063857 0.1295321 34.790 < 2e-16 ***
ORIGIN_GRID_ID1939 5.0931635 0.1295203 39.323 < 2e-16 ***
ORIGIN_GRID_ID1942 1.0266151 0.1374728 7.468 8.16e-14 ***
ORIGIN_GRID_ID1959 3.4108415 0.1297730 26.283 < 2e-16 ***
ORIGIN_GRID_ID1960 5.3846030 0.1294846 41.585 < 2e-16 ***
ORIGIN_GRID_ID1961 3.8209126 0.1296537 29.470 < 2e-16 ***
ORIGIN_GRID_ID1962 4.8649895 0.1295275 37.560 < 2e-16 ***
ORIGIN_GRID_ID1964 0.1833982 0.1555282 1.179 0.238320
ORIGIN_GRID_ID1979 3.7065226 0.1297238 28.572 < 2e-16 ***
ORIGIN_GRID_ID1980 2.0295434 0.1303081 15.575 < 2e-16 ***
ORIGIN_GRID_ID1981 4.4990961 0.1295291 34.734 < 2e-16 ***
ORIGIN_GRID_ID1982 3.5070548 0.1299789 26.982 < 2e-16 ***
ORIGIN_GRID_ID1983 4.7746379 0.1295308 36.861 < 2e-16 ***
ORIGIN_GRID_ID1984 3.4708003 0.1297052 26.759 < 2e-16 ***
ORIGIN_GRID_ID1985 4.2648741 0.1296134 32.905 < 2e-16 ***
ORIGIN_GRID_ID2001 4.0140921 0.1295989 30.973 < 2e-16 ***
ORIGIN_GRID_ID2002 4.5855558 0.1295114 35.407 < 2e-16 ***
ORIGIN_GRID_ID2003 4.2399434 0.1295580 32.726 < 2e-16 ***
ORIGIN_GRID_ID2004 4.8402128 0.1295269 37.368 < 2e-16 ***
ORIGIN_GRID_ID2005 4.7454706 0.1295219 36.638 < 2e-16 ***
ORIGIN_GRID_ID2006 3.2794634 0.1298219 25.261 < 2e-16 ***
ORIGIN_GRID_ID2007 2.7363616 0.1305374 20.962 < 2e-16 ***
ORIGIN_GRID_ID2022 4.3706162 0.1296021 33.723 < 2e-16 ***
ORIGIN_GRID_ID2023 4.8479000 0.1295080 37.433 < 2e-16 ***
ORIGIN_GRID_ID2024 4.1465952 0.1295481 32.008 < 2e-16 ***
ORIGIN_GRID_ID2025 4.2128958 0.1295406 32.522 < 2e-16 ***
ORIGIN_GRID_ID2026 2.9159675 0.1300143 22.428 < 2e-16 ***
ORIGIN_GRID_ID2027 5.1546894 0.1295166 39.799 < 2e-16 ***
ORIGIN_GRID_ID2043 3.7276268 0.1297016 28.740 < 2e-16 ***
ORIGIN_GRID_ID2044 4.4557696 0.1295263 34.400 < 2e-16 ***
ORIGIN_GRID_ID2045 -0.0252116 0.1514517 -0.166 0.867790
ORIGIN_GRID_ID2046 4.3936796 0.1295158 33.924 < 2e-16 ***
ORIGIN_GRID_ID2047 4.2289789 0.1295650 32.640 < 2e-16 ***
ORIGIN_GRID_ID2048 4.4756824 0.1295400 34.551 < 2e-16 ***
ORIGIN_GRID_ID2049 3.5545493 0.1302061 27.299 < 2e-16 ***
ORIGIN_GRID_ID2064 4.4257907 0.1295551 34.161 < 2e-16 ***
ORIGIN_GRID_ID2065 2.8714782 0.1297673 22.128 < 2e-16 ***
ORIGIN_GRID_ID2066 2.2380805 0.1319817 16.958 < 2e-16 ***
ORIGIN_GRID_ID2067 5.6471900 0.1294808 43.614 < 2e-16 ***
ORIGIN_GRID_ID2068 4.0330370 0.1296527 31.106 < 2e-16 ***
ORIGIN_GRID_ID2069 4.3544836 0.1295775 33.605 < 2e-16 ***
ORIGIN_GRID_ID2085 3.2942545 0.1298439 25.371 < 2e-16 ***
ORIGIN_GRID_ID2086 4.7240317 0.1295209 36.473 < 2e-16 ***
ORIGIN_GRID_ID2087 3.3368295 0.1296817 25.731 < 2e-16 ***
ORIGIN_GRID_ID2088 4.0634901 0.1295417 31.368 < 2e-16 ***
ORIGIN_GRID_ID2089 3.8436392 0.1296279 29.651 < 2e-16 ***
ORIGIN_GRID_ID2090 5.3432354 0.1295000 41.261 < 2e-16 ***
ORIGIN_GRID_ID2091 0.6235882 0.1490991 4.182 2.88e-05 ***
ORIGIN_GRID_ID2105 1.3623610 0.1729868 7.876 3.39e-15 ***
ORIGIN_GRID_ID2106 1.6340259 0.1310477 12.469 < 2e-16 ***
ORIGIN_GRID_ID2107 2.7415995 0.1298228 21.118 < 2e-16 ***
ORIGIN_GRID_ID2108 4.0208009 0.1295834 31.029 < 2e-16 ***
ORIGIN_GRID_ID2109 4.1325734 0.1295375 31.903 < 2e-16 ***
ORIGIN_GRID_ID2110 3.5800117 0.1296758 27.607 < 2e-16 ***
ORIGIN_GRID_ID2111 0.6703908 0.1387091 4.833 1.34e-06 ***
ORIGIN_GRID_ID2128 2.4306723 0.1303459 18.648 < 2e-16 ***
ORIGIN_GRID_ID2129 1.8785665 0.1304798 14.397 < 2e-16 ***
ORIGIN_GRID_ID2130 4.5887682 0.1295138 35.431 < 2e-16 ***
ORIGIN_GRID_ID2131 4.9236412 0.1295363 38.010 < 2e-16 ***
ORIGIN_GRID_ID2132 3.8498815 0.1296064 29.704 < 2e-16 ***
ORIGIN_GRID_ID2148 3.3494736 0.1300216 25.761 < 2e-16 ***
ORIGIN_GRID_ID2149 1.9096252 0.1305447 14.628 < 2e-16 ***
ORIGIN_GRID_ID2150 4.4644351 0.1295413 34.463 < 2e-16 ***
ORIGIN_GRID_ID2151 4.9418563 0.1295022 38.160 < 2e-16 ***
ORIGIN_GRID_ID2152 5.1147815 0.1295103 39.493 < 2e-16 ***
ORIGIN_GRID_ID2153 4.4674996 0.1295785 34.477 < 2e-16 ***
ORIGIN_GRID_ID2171 3.4510395 0.1296779 26.612 < 2e-16 ***
ORIGIN_GRID_ID2172 3.5810833 0.1297110 27.608 < 2e-16 ***
ORIGIN_GRID_ID2173 4.1171571 0.1295601 31.778 < 2e-16 ***
ORIGIN_GRID_ID2174 4.3942067 0.1295685 33.914 < 2e-16 ***
ORIGIN_GRID_ID2191 3.0972812 0.1299223 23.839 < 2e-16 ***
ORIGIN_GRID_ID2192 2.8408429 0.1299882 21.855 < 2e-16 ***
ORIGIN_GRID_ID2193 3.7704971 0.1296142 29.090 < 2e-16 ***
ORIGIN_GRID_ID2194 4.2148072 0.1295622 32.531 < 2e-16 ***
ORIGIN_GRID_ID2195 3.5860358 0.1313653 27.298 < 2e-16 ***
ORIGIN_GRID_ID2212 0.3419295 0.1659173 2.061 0.039318 *
ORIGIN_GRID_ID2213 0.7145195 0.1369915 5.216 1.83e-07 ***
ORIGIN_GRID_ID2214 1.2862755 0.1325062 9.707 < 2e-16 ***
ORIGIN_GRID_ID2215 3.8474378 0.1296565 29.674 < 2e-16 ***
ORIGIN_GRID_ID2216 2.8687319 0.1299585 22.074 < 2e-16 ***
ORIGIN_GRID_ID2233 0.9610781 0.1386201 6.933 4.11e-12 ***
ORIGIN_GRID_ID2234 2.6883173 0.1311526 20.498 < 2e-16 ***
ORIGIN_GRID_ID2235 2.6415543 0.1302306 20.284 < 2e-16 ***
ORIGIN_GRID_ID2236 2.6581568 0.1301256 20.428 < 2e-16 ***
ORIGIN_GRID_ID2237 0.3775735 0.1434775 2.632 0.008499 **
ORIGIN_GRID_ID2256 0.3942047 0.1369451 2.879 0.003995 **
ORIGIN_GRID_ID2257 2.3998838 0.1310740 18.309 < 2e-16 ***
ORIGIN_GRID_ID2258 1.9301415 0.1305385 14.786 < 2e-16 ***
ORIGIN_GRID_ID2259 1.4100794 0.1354683 10.409 < 2e-16 ***
ORIGIN_GRID_ID2277 2.5821183 0.1350180 19.124 < 2e-16 ***
ORIGIN_GRID_ID2278 2.9734869 0.1304980 22.786 < 2e-16 ***
ORIGIN_GRID_ID2279 1.5464699 0.1311154 11.795 < 2e-16 ***
ORIGIN_GRID_ID2280 -0.6809315 0.1861265 -3.658 0.000254 ***
ORIGIN_GRID_ID2297 4.3897509 0.1298261 33.813 < 2e-16 ***
ORIGIN_GRID_ID2300 0.2711612 0.1471300 1.843 0.065328 .
ORIGIN_GRID_ID2301 1.8757095 0.1310259 14.316 < 2e-16 ***
ORIGIN_GRID_ID2318 2.4721615 0.1309733 18.875 < 2e-16 ***
ORIGIN_GRID_ID2319 3.0739636 0.1299723 23.651 < 2e-16 ***
ORIGIN_GRID_ID2322 2.9770665 0.1301165 22.880 < 2e-16 ***
ORIGIN_GRID_ID2337 4.0237606 0.1307062 30.785 < 2e-16 ***
ORIGIN_GRID_ID2341 3.4439661 0.1298996 26.513 < 2e-16 ***
ORIGIN_GRID_ID2343 2.2916504 0.1303094 17.586 < 2e-16 ***
ORIGIN_GRID_ID2361 3.1646330 0.1301059 24.324 < 2e-16 ***
ORIGIN_GRID_ID2364 -0.9603101 0.1610705 -5.962 2.49e-09 ***
ORIGIN_GRID_ID2379 3.3998841 0.1311041 25.933 < 2e-16 ***
ORIGIN_GRID_ID2384 2.0344487 0.1306617 15.570 < 2e-16 ***
ORIGIN_GRID_ID2405 1.6650632 0.1308085 12.729 < 2e-16 ***
ORIGIN_GRID_ID2406 0.4187059 0.1355139 3.090 0.002003 **
ORIGIN_GRID_ID2426 1.1432452 0.1337364 8.548 < 2e-16 ***
ORIGIN_GRID_ID2427 2.9732093 0.1300135 22.868 < 2e-16 ***
ORIGIN_GRID_ID2505 3.2377742 0.1375560 23.538 < 2e-16 ***
DESTIN_GRID_ID44 1.4622128 0.0599515 24.390 < 2e-16 ***
DESTIN_GRID_ID46 0.5319231 0.0595110 8.938 < 2e-16 ***
DESTIN_GRID_ID66 -0.3327032 0.0737214 -4.513 6.39e-06 ***
DESTIN_GRID_ID67 0.4680626 0.0576879 8.114 4.91e-16 ***
DESTIN_GRID_ID68 0.1769068 0.0596427 2.966 0.003016 **
DESTIN_GRID_ID86 0.5438841 0.0661281 8.225 < 2e-16 ***
DESTIN_GRID_ID87 -2.8337114 0.1051549 -26.948 < 2e-16 ***
DESTIN_GRID_ID88 -0.0324119 0.0586927 -0.552 0.580790
DESTIN_GRID_ID89 -0.5638370 0.0601866 -9.368 < 2e-16 ***
DESTIN_GRID_ID90 -3.6895825 0.7095099 -5.200 1.99e-07 ***
DESTIN_GRID_ID109 -0.3518091 0.0610847 -5.759 8.44e-09 ***
DESTIN_GRID_ID110 -3.3039875 0.1302717 -25.362 < 2e-16 ***
DESTIN_GRID_ID111 1.1158166 0.0570269 19.567 < 2e-16 ***
DESTIN_GRID_ID112 -2.3570345 0.0649361 -36.298 < 2e-16 ***
DESTIN_GRID_ID128 1.1998830 0.0610711 19.647 < 2e-16 ***
DESTIN_GRID_ID129 -4.2827829 0.1496826 -28.612 < 2e-16 ***
DESTIN_GRID_ID130 -0.5643472 0.0605581 -9.319 < 2e-16 ***
DESTIN_GRID_ID131 -1.2821698 0.0602755 -21.272 < 2e-16 ***
DESTIN_GRID_ID132 -0.7649506 0.0576400 -13.271 < 2e-16 ***
DESTIN_GRID_ID133 -0.6621012 0.0570089 -11.614 < 2e-16 ***
DESTIN_GRID_ID134 -0.5275712 0.0568430 -9.281 < 2e-16 ***
DESTIN_GRID_ID150 -0.1431481 0.0654261 -2.188 0.028674 *
DESTIN_GRID_ID151 -0.4600586 0.0603655 -7.621 2.51e-14 ***
DESTIN_GRID_ID152 0.4893470 0.0578572 8.458 < 2e-16 ***
DESTIN_GRID_ID153 0.0399034 0.0575502 0.693 0.488079
DESTIN_GRID_ID154 -2.1150821 0.0625220 -33.829 < 2e-16 ***
DESTIN_GRID_ID155 -1.7234705 0.0590418 -29.191 < 2e-16 ***
DESTIN_GRID_ID156 -1.5943735 0.0601229 -26.519 < 2e-16 ***
DESTIN_GRID_ID172 -1.5253142 0.0719028 -21.214 < 2e-16 ***
DESTIN_GRID_ID174 -1.0284546 0.0579102 -17.759 < 2e-16 ***
DESTIN_GRID_ID175 -0.6188958 0.0566492 -10.925 < 2e-16 ***
DESTIN_GRID_ID176 -1.9698626 0.0631652 -31.186 < 2e-16 ***
DESTIN_GRID_ID195 -2.3265669 0.0638224 -36.454 < 2e-16 ***
DESTIN_GRID_ID196 -0.8845114 0.0566373 -15.617 < 2e-16 ***
DESTIN_GRID_ID197 -4.0916426 0.0951996 -42.980 < 2e-16 ***
DESTIN_GRID_ID215 -0.3756721 0.0633979 -5.926 3.11e-09 ***
DESTIN_GRID_ID216 -0.5098475 0.0579487 -8.798 < 2e-16 ***
DESTIN_GRID_ID217 -0.1795512 0.0565084 -3.177 0.001486 **
DESTIN_GRID_ID237 -2.4806836 0.0637294 -38.925 < 2e-16 ***
DESTIN_GRID_ID238 -1.4885385 0.0578225 -25.743 < 2e-16 ***
DESTIN_GRID_ID239 -1.7701573 0.0639681 -27.672 < 2e-16 ***
DESTIN_GRID_ID257 0.4734847 0.0582220 8.132 4.21e-16 ***
DESTIN_GRID_ID258 -1.4019130 0.0590884 -23.726 < 2e-16 ***
DESTIN_GRID_ID259 -0.2953099 0.0570382 -5.177 2.25e-07 ***
DESTIN_GRID_ID278 0.8453824 0.0576984 14.652 < 2e-16 ***
DESTIN_GRID_ID279 -0.8793005 0.0574061 -15.317 < 2e-16 ***
DESTIN_GRID_ID280 -0.6191074 0.0572356 -10.817 < 2e-16 ***
DESTIN_GRID_ID298 -3.8349063 0.1609002 -23.834 < 2e-16 ***
DESTIN_GRID_ID299 -0.5927369 0.0581469 -10.194 < 2e-16 ***
DESTIN_GRID_ID300 -1.1655987 0.0584292 -19.949 < 2e-16 ***
DESTIN_GRID_ID320 0.7312798 0.0576172 12.692 < 2e-16 ***
DESTIN_GRID_ID321 -1.5308394 0.0608580 -25.154 < 2e-16 ***
DESTIN_GRID_ID322 -0.2797520 0.0571089 -4.899 9.65e-07 ***
DESTIN_GRID_ID340 1.4438309 0.0569556 25.350 < 2e-16 ***
DESTIN_GRID_ID341 -0.0510694 0.0571574 -0.893 0.371597
DESTIN_GRID_ID342 -0.4052381 0.0568450 -7.129 1.01e-12 ***
DESTIN_GRID_ID363 -0.4201841 0.0574597 -7.313 2.62e-13 ***
DESTIN_GRID_ID364 -0.4159469 0.0564053 -7.374 1.65e-13 ***
DESTIN_GRID_ID383 0.5944577 0.0566152 10.500 < 2e-16 ***
DESTIN_GRID_ID384 -0.6047747 0.0564955 -10.705 < 2e-16 ***
DESTIN_GRID_ID385 -1.5860762 0.0579197 -27.384 < 2e-16 ***
DESTIN_GRID_ID404 0.7255789 0.0572961 12.664 < 2e-16 ***
DESTIN_GRID_ID405 -0.0059071 0.0568763 -0.104 0.917281
DESTIN_GRID_ID406 0.3258141 0.0561275 5.805 6.44e-09 ***
DESTIN_GRID_ID407 -0.1879321 0.0567586 -3.311 0.000929 ***
DESTIN_GRID_ID408 0.9873473 0.0561921 17.571 < 2e-16 ***
DESTIN_GRID_ID425 -1.6470203 0.0611848 -26.919 < 2e-16 ***
DESTIN_GRID_ID426 -1.0627853 0.0568112 -18.707 < 2e-16 ***
DESTIN_GRID_ID427 -3.7286999 0.0618371 -60.299 < 2e-16 ***
DESTIN_GRID_ID428 -1.1507027 0.0571899 -20.121 < 2e-16 ***
DESTIN_GRID_ID429 -1.3421740 0.0608727 -22.049 < 2e-16 ***
DESTIN_GRID_ID446 -0.4338243 0.0605225 -7.168 7.61e-13 ***
DESTIN_GRID_ID447 -1.2630749 0.0584555 -21.607 < 2e-16 ***
DESTIN_GRID_ID448 -1.5744509 0.0570779 -27.584 < 2e-16 ***
DESTIN_GRID_ID449 -0.9369461 0.0563927 -16.615 < 2e-16 ***
DESTIN_GRID_ID450 -1.5402983 0.0573846 -26.842 < 2e-16 ***
DESTIN_GRID_ID468 -0.9105406 0.0569312 -15.994 < 2e-16 ***
DESTIN_GRID_ID469 -1.4550938 0.0565705 -25.722 < 2e-16 ***
DESTIN_GRID_ID470 -1.2622034 0.0564314 -22.367 < 2e-16 ***
DESTIN_GRID_ID471 -1.0928520 0.0585893 -18.653 < 2e-16 ***
DESTIN_GRID_ID488 -0.5084583 0.0602379 -8.441 < 2e-16 ***
DESTIN_GRID_ID489 -2.5912764 0.0737440 -35.139 < 2e-16 ***
DESTIN_GRID_ID490 -0.6759888 0.0565735 -11.949 < 2e-16 ***
DESTIN_GRID_ID491 -3.1600977 0.0584058 -54.106 < 2e-16 ***
DESTIN_GRID_ID493 -3.4993139 0.0743157 -47.087 < 2e-16 ***
DESTIN_GRID_ID494 -1.7057315 0.0605710 -28.161 < 2e-16 ***
DESTIN_GRID_ID509 -0.1488279 0.0580342 -2.564 0.010333 *
DESTIN_GRID_ID510 -0.4222912 0.0568420 -7.429 1.09e-13 ***
DESTIN_GRID_ID511 -1.2009361 0.0563544 -21.310 < 2e-16 ***
DESTIN_GRID_ID512 -1.5163061 0.0563838 -26.893 < 2e-16 ***
DESTIN_GRID_ID513 -0.3590575 0.0565775 -6.346 2.21e-10 ***
DESTIN_GRID_ID514 -0.6640037 0.0572309 -11.602 < 2e-16 ***
DESTIN_GRID_ID515 -2.1628762 0.0645543 -33.505 < 2e-16 ***
DESTIN_GRID_ID530 -0.7680863 0.0630723 -12.178 < 2e-16 ***
DESTIN_GRID_ID531 1.4426398 0.0562877 25.630 < 2e-16 ***
DESTIN_GRID_ID532 -0.9595440 0.0566302 -16.944 < 2e-16 ***
DESTIN_GRID_ID533 0.1998578 0.0560223 3.567 0.000360 ***
DESTIN_GRID_ID534 -1.2910072 0.0563850 -22.896 < 2e-16 ***
DESTIN_GRID_ID536 -1.5778461 0.0589071 -26.785 < 2e-16 ***
DESTIN_GRID_ID537 -2.3645345 0.0658871 -35.888 < 2e-16 ***
DESTIN_GRID_ID538 -2.6994884 0.0714056 -37.805 < 2e-16 ***
DESTIN_GRID_ID539 -5.0222674 0.2730828 -18.391 < 2e-16 ***
DESTIN_GRID_ID551 -0.1595113 0.0587433 -2.715 0.006620 **
DESTIN_GRID_ID552 0.2438787 0.0569888 4.279 1.87e-05 ***
DESTIN_GRID_ID553 -1.7241873 0.0566192 -30.452 < 2e-16 ***
DESTIN_GRID_ID554 -1.7964567 0.0564029 -31.850 < 2e-16 ***
DESTIN_GRID_ID555 -0.5469614 0.0564838 -9.684 < 2e-16 ***
DESTIN_GRID_ID559 -2.8154968 0.0775956 -36.284 < 2e-16 ***
DESTIN_GRID_ID560 -0.4795559 0.0584989 -8.198 2.45e-16 ***
DESTIN_GRID_ID561 -2.8622381 0.0877717 -32.610 < 2e-16 ***
DESTIN_GRID_ID572 -1.0767462 0.0657332 -16.381 < 2e-16 ***
DESTIN_GRID_ID573 0.6074606 0.0569370 10.669 < 2e-16 ***
DESTIN_GRID_ID574 -1.2140643 0.0581368 -20.883 < 2e-16 ***
DESTIN_GRID_ID575 1.2306789 0.0559789 21.985 < 2e-16 ***
DESTIN_GRID_ID576 -1.4025293 0.0563251 -24.901 < 2e-16 ***
DESTIN_GRID_ID578 -4.7699991 0.1209517 -39.437 < 2e-16 ***
DESTIN_GRID_ID582 -3.0697017 0.0844692 -36.341 < 2e-16 ***
DESTIN_GRID_ID583 -4.9468632 0.3820978 -12.947 < 2e-16 ***
DESTIN_GRID_ID584 -1.4975742 0.0666729 -22.462 < 2e-16 ***
DESTIN_GRID_ID593 -1.7095605 0.0615417 -27.779 < 2e-16 ***
DESTIN_GRID_ID594 -0.3950048 0.0577030 -6.845 7.62e-12 ***
DESTIN_GRID_ID595 -0.6066975 0.0562625 -10.783 < 2e-16 ***
DESTIN_GRID_ID596 -1.1948830 0.0561848 -21.267 < 2e-16 ***
DESTIN_GRID_ID597 -1.6667549 0.0580980 -28.689 < 2e-16 ***
DESTIN_GRID_ID603 -2.6222893 0.0769880 -34.061 < 2e-16 ***
DESTIN_GRID_ID604 -2.1614324 0.0755896 -28.594 < 2e-16 ***
DESTIN_GRID_ID615 -1.3122287 0.0578817 -22.671 < 2e-16 ***
DESTIN_GRID_ID616 -0.8295129 0.0566982 -14.630 < 2e-16 ***
DESTIN_GRID_ID617 -1.9204044 0.0567105 -33.863 < 2e-16 ***
DESTIN_GRID_ID618 -1.4180101 0.0563660 -25.157 < 2e-16 ***
DESTIN_GRID_ID620 -1.2680107 0.0571280 -22.196 < 2e-16 ***
DESTIN_GRID_ID637 -1.3320811 0.0570325 -23.357 < 2e-16 ***
DESTIN_GRID_ID638 -1.3965893 0.0563041 -24.804 < 2e-16 ***
DESTIN_GRID_ID657 0.0234156 0.0564124 0.415 0.678085
DESTIN_GRID_ID658 -0.6912529 0.0563091 -12.276 < 2e-16 ***
DESTIN_GRID_ID659 -0.9990878 0.0562712 -17.755 < 2e-16 ***
DESTIN_GRID_ID660 -0.5976885 0.0561318 -10.648 < 2e-16 ***
DESTIN_GRID_ID662 -1.1652011 0.0573422 -20.320 < 2e-16 ***
DESTIN_GRID_ID677 0.0859237 0.0567691 1.514 0.130137
DESTIN_GRID_ID678 -1.8271131 0.0577241 -31.653 < 2e-16 ***
DESTIN_GRID_ID679 -0.4007848 0.0561970 -7.132 9.91e-13 ***
DESTIN_GRID_ID680 1.0449607 0.0560168 18.654 < 2e-16 ***
DESTIN_GRID_ID681 -2.8415194 0.0596450 -47.641 < 2e-16 ***
DESTIN_GRID_ID699 -0.4961318 0.0567089 -8.749 < 2e-16 ***
DESTIN_GRID_ID700 -1.0373932 0.0564457 -18.379 < 2e-16 ***
DESTIN_GRID_ID701 -3.5160097 0.0605672 -58.051 < 2e-16 ***
DESTIN_GRID_ID702 -0.8112494 0.0561865 -14.439 < 2e-16 ***
DESTIN_GRID_ID704 -1.6847881 0.0571004 -29.506 < 2e-16 ***
DESTIN_GRID_ID722 -1.5672146 0.0566943 -27.643 < 2e-16 ***
DESTIN_GRID_ID725 -3.8523162 0.0624671 -61.669 < 2e-16 ***
DESTIN_GRID_ID741 0.0538719 0.0564628 0.954 0.340026
DESTIN_GRID_ID743 -3.6883509 0.0612006 -60.267 < 2e-16 ***
DESTIN_GRID_ID744 -0.7473183 0.0561943 -13.299 < 2e-16 ***
DESTIN_GRID_ID761 0.3483976 0.0566367 6.151 7.68e-10 ***
DESTIN_GRID_ID762 -1.7251745 0.0577563 -29.870 < 2e-16 ***
DESTIN_GRID_ID763 -3.3149530 0.0602145 -55.052 < 2e-16 ***
DESTIN_GRID_ID764 -0.2336378 0.0560895 -4.165 3.11e-05 ***
DESTIN_GRID_ID765 -1.0803201 0.0568283 -19.010 < 2e-16 ***
DESTIN_GRID_ID767 -1.3636823 0.0564482 -24.158 < 2e-16 ***
DESTIN_GRID_ID772 -2.2990853 0.0696955 -32.988 < 2e-16 ***
DESTIN_GRID_ID784 -3.1348465 0.0605057 -51.811 < 2e-16 ***
DESTIN_GRID_ID785 -1.1852740 0.0562697 -21.064 < 2e-16 ***
DESTIN_GRID_ID786 -1.0708303 0.0562012 -19.053 < 2e-16 ***
DESTIN_GRID_ID787 -1.8986629 0.0570915 -33.256 < 2e-16 ***
DESTIN_GRID_ID788 -3.4009293 0.0585568 -58.079 < 2e-16 ***
DESTIN_GRID_ID789 -3.5721654 0.0590489 -60.495 < 2e-16 ***
DESTIN_GRID_ID803 -0.8593171 0.0577451 -14.881 < 2e-16 ***
DESTIN_GRID_ID804 -0.3348720 0.0563503 -5.943 2.80e-09 ***
DESTIN_GRID_ID805 0.5964338 0.0560434 10.642 < 2e-16 ***
DESTIN_GRID_ID806 -1.2869154 0.0562852 -22.864 < 2e-16 ***
DESTIN_GRID_ID807 -1.2651589 0.0564801 -22.400 < 2e-16 ***
DESTIN_GRID_ID808 -2.6763702 0.0588314 -45.492 < 2e-16 ***
DESTIN_GRID_ID809 -1.4835566 0.0562581 -26.371 < 2e-16 ***
DESTIN_GRID_ID810 -1.8101062 0.0566401 -31.958 < 2e-16 ***
DESTIN_GRID_ID814 -1.2165927 0.0598064 -20.342 < 2e-16 ***
DESTIN_GRID_ID819 -0.3467579 0.0584523 -5.932 2.99e-09 ***
DESTIN_GRID_ID824 -0.6418792 0.0577056 -11.123 < 2e-16 ***
DESTIN_GRID_ID826 -0.9411166 0.0563142 -16.712 < 2e-16 ***
DESTIN_GRID_ID827 -1.3116627 0.0563755 -23.267 < 2e-16 ***
DESTIN_GRID_ID828 -1.1460946 0.0562207 -20.386 < 2e-16 ***
DESTIN_GRID_ID829 -1.5970109 0.0566019 -28.215 < 2e-16 ***
DESTIN_GRID_ID830 -3.1232633 0.0579205 -53.923 < 2e-16 ***
DESTIN_GRID_ID831 0.4269597 0.0560451 7.618 2.57e-14 ***
DESTIN_GRID_ID832 0.0461247 0.0561467 0.822 0.411360
DESTIN_GRID_ID835 -1.6421765 0.0598943 -27.418 < 2e-16 ***
DESTIN_GRID_ID844 -0.9214870 0.0590060 -15.617 < 2e-16 ***
DESTIN_GRID_ID846 -0.9842465 0.0564522 -17.435 < 2e-16 ***
DESTIN_GRID_ID847 -0.2561780 0.0561672 -4.561 5.09e-06 ***
DESTIN_GRID_ID848 -1.4960803 0.0563771 -26.537 < 2e-16 ***
DESTIN_GRID_ID849 -2.1459733 0.0566145 -37.905 < 2e-16 ***
DESTIN_GRID_ID850 -1.3163545 0.0562619 -23.397 < 2e-16 ***
DESTIN_GRID_ID851 -1.9197074 0.0563961 -34.040 < 2e-16 ***
DESTIN_GRID_ID852 -1.9727214 0.0566366 -34.831 < 2e-16 ***
DESTIN_GRID_ID853 -0.9807193 0.0567874 -17.270 < 2e-16 ***
DESTIN_GRID_ID854 -0.8880022 0.0578351 -15.354 < 2e-16 ***
DESTIN_GRID_ID855 -1.8142613 0.0595730 -30.454 < 2e-16 ***
DESTIN_GRID_ID856 -2.4214017 0.0646467 -37.456 < 2e-16 ***
DESTIN_GRID_ID866 -0.1434185 0.0568683 -2.522 0.011671 *
DESTIN_GRID_ID867 0.3727737 0.0561646 6.637 3.20e-11 ***
DESTIN_GRID_ID868 -0.1434619 0.0562517 -2.550 0.010761 *
DESTIN_GRID_ID869 0.7646220 0.0562223 13.600 < 2e-16 ***
DESTIN_GRID_ID870 0.2566817 0.0560465 4.580 4.65e-06 ***
DESTIN_GRID_ID871 0.1671360 0.0561276 2.978 0.002903 **
DESTIN_GRID_ID872 -1.4625219 0.0563177 -25.969 < 2e-16 ***
DESTIN_GRID_ID873 -1.9107695 0.0566782 -33.713 < 2e-16 ***
DESTIN_GRID_ID874 -3.1275384 0.0577000 -54.203 < 2e-16 ***
DESTIN_GRID_ID875 -2.3732670 0.0624043 -38.031 < 2e-16 ***
DESTIN_GRID_ID876 -2.0164697 0.0591586 -34.086 < 2e-16 ***
DESTIN_GRID_ID877 -1.3931346 0.0578846 -24.067 < 2e-16 ***
DESTIN_GRID_ID887 -0.9652999 0.0567153 -17.020 < 2e-16 ***
DESTIN_GRID_ID888 -2.2232136 0.0578966 -38.400 < 2e-16 ***
DESTIN_GRID_ID889 -1.4981733 0.0574781 -26.065 < 2e-16 ***
DESTIN_GRID_ID890 -0.6358517 0.0562075 -11.313 < 2e-16 ***
DESTIN_GRID_ID891 -2.1904464 0.0580561 -37.730 < 2e-16 ***
DESTIN_GRID_ID893 -0.9200054 0.0561581 -16.382 < 2e-16 ***
DESTIN_GRID_ID894 -2.4994244 0.0571422 -43.740 < 2e-16 ***
DESTIN_GRID_ID895 -1.2894161 0.0567225 -22.732 < 2e-16 ***
DESTIN_GRID_ID896 -3.7202880 0.0653727 -56.909 < 2e-16 ***
DESTIN_GRID_ID897 -3.6980696 0.0643985 -57.425 < 2e-16 ***
DESTIN_GRID_ID898 -1.3867301 0.0584669 -23.718 < 2e-16 ***
DESTIN_GRID_ID908 -0.0739733 0.0570418 -1.297 0.194691
DESTIN_GRID_ID909 -0.9744166 0.0563500 -17.292 < 2e-16 ***
DESTIN_GRID_ID910 -1.9161865 0.0571994 -33.500 < 2e-16 ***
DESTIN_GRID_ID911 0.1594489 0.0561284 2.841 0.004500 **
DESTIN_GRID_ID912 -1.6585197 0.0565504 -29.328 < 2e-16 ***
DESTIN_GRID_ID915 -1.5177522 0.0563125 -26.952 < 2e-16 ***
DESTIN_GRID_ID917 -0.0641671 0.0562612 -1.141 0.254070
DESTIN_GRID_ID918 -4.3304031 0.0688900 -62.860 < 2e-16 ***
DESTIN_GRID_ID919 -2.7253094 0.0583697 -46.691 < 2e-16 ***
DESTIN_GRID_ID928 -2.0983684 0.0591372 -35.483 < 2e-16 ***
DESTIN_GRID_ID929 -1.2131255 0.0564972 -21.472 < 2e-16 ***
DESTIN_GRID_ID930 0.0504921 0.0560985 0.900 0.368088
DESTIN_GRID_ID931 -1.4558836 0.0569942 -25.544 < 2e-16 ***
DESTIN_GRID_ID932 -3.1623216 0.0614007 -51.503 < 2e-16 ***
DESTIN_GRID_ID933 -1.1740518 0.0565786 -20.751 < 2e-16 ***
DESTIN_GRID_ID934 -1.3969944 0.0565134 -24.720 < 2e-16 ***
DESTIN_GRID_ID935 0.4444607 0.0560350 7.932 2.16e-15 ***
DESTIN_GRID_ID938 -5.2475266 0.1535294 -34.179 < 2e-16 ***
DESTIN_GRID_ID939 0.5434187 0.0561235 9.683 < 2e-16 ***
DESTIN_GRID_ID940 -3.4778278 0.0597676 -58.189 < 2e-16 ***
DESTIN_GRID_ID949 -1.7253343 0.0581095 -29.691 < 2e-16 ***
DESTIN_GRID_ID950 0.2499424 0.0562158 4.446 8.74e-06 ***
DESTIN_GRID_ID951 0.9727551 0.0560382 17.359 < 2e-16 ***
DESTIN_GRID_ID952 -0.5080668 0.0565274 -8.988 < 2e-16 ***
DESTIN_GRID_ID953 -1.0427091 0.0567066 -18.388 < 2e-16 ***
DESTIN_GRID_ID954 -2.9670241 0.0587723 -50.483 < 2e-16 ***
DESTIN_GRID_ID955 -0.2175132 0.0561621 -3.873 0.000108 ***
DESTIN_GRID_ID956 -2.1714712 0.0568037 -38.228 < 2e-16 ***
DESTIN_GRID_ID957 -2.1335552 0.0568199 -37.549 < 2e-16 ***
DESTIN_GRID_ID959 -1.4844931 0.0594099 -24.987 < 2e-16 ***
DESTIN_GRID_ID961 -1.9445067 0.0573970 -33.878 < 2e-16 ***
DESTIN_GRID_ID962 -0.1648276 0.0563306 -2.926 0.003433 **
DESTIN_GRID_ID970 -0.8118304 0.0565568 -14.354 < 2e-16 ***
DESTIN_GRID_ID971 -0.3472479 0.0561691 -6.182 6.32e-10 ***
DESTIN_GRID_ID972 -1.2177137 0.0565049 -21.551 < 2e-16 ***
DESTIN_GRID_ID974 -1.6177109 0.0571216 -28.320 < 2e-16 ***
DESTIN_GRID_ID975 -2.8746344 0.0587338 -48.943 < 2e-16 ***
DESTIN_GRID_ID976 -2.1342346 0.0570368 -37.419 < 2e-16 ***
DESTIN_GRID_ID977 -1.7854284 0.0564092 -31.651 < 2e-16 ***
DESTIN_GRID_ID978 -2.1838612 0.0572031 -38.177 < 2e-16 ***
DESTIN_GRID_ID982 -2.7834906 0.0571897 -48.671 < 2e-16 ***
DESTIN_GRID_ID983 0.1029932 0.0562727 1.830 0.067212 .
DESTIN_GRID_ID984 1.5165317 0.0564781 26.852 < 2e-16 ***
DESTIN_GRID_ID991 -0.3316807 0.0564567 -5.875 4.23e-09 ***
DESTIN_GRID_ID992 -0.4979542 0.0563631 -8.835 < 2e-16 ***
DESTIN_GRID_ID993 -1.7948383 0.0568617 -31.565 < 2e-16 ***
DESTIN_GRID_ID994 -1.8754811 0.0573394 -32.708 < 2e-16 ***
DESTIN_GRID_ID995 -1.2469841 0.0566539 -22.011 < 2e-16 ***
DESTIN_GRID_ID996 -1.8807386 0.0572830 -32.832 < 2e-16 ***
DESTIN_GRID_ID997 -1.5531018 0.0575535 -26.985 < 2e-16 ***
DESTIN_GRID_ID998 -1.2207008 0.0563539 -21.661 < 2e-16 ***
DESTIN_GRID_ID999 -2.4060880 0.0570858 -42.149 < 2e-16 ***
DESTIN_GRID_ID1001 -1.2568980 0.0581097 -21.630 < 2e-16 ***
DESTIN_GRID_ID1003 0.0845453 0.0561008 1.507 0.131804
DESTIN_GRID_ID1004 -1.4434659 0.0562940 -25.642 < 2e-16 ***
DESTIN_GRID_ID1011 -0.7710926 0.0573250 -13.451 < 2e-16 ***
DESTIN_GRID_ID1012 0.1740565 0.0565292 3.079 0.002077 **
DESTIN_GRID_ID1013 -0.4996487 0.0564257 -8.855 < 2e-16 ***
DESTIN_GRID_ID1014 -2.5187696 0.0588508 -42.799 < 2e-16 ***
DESTIN_GRID_ID1015 -0.0651193 0.0562178 -1.158 0.246725
DESTIN_GRID_ID1016 0.2543315 0.0561192 4.532 5.84e-06 ***
DESTIN_GRID_ID1018 -2.1017743 0.0574301 -36.597 < 2e-16 ***
DESTIN_GRID_ID1019 -1.3213453 0.0563789 -23.437 < 2e-16 ***
DESTIN_GRID_ID1023 -2.1655230 0.0577327 -37.509 < 2e-16 ***
DESTIN_GRID_ID1024 -1.0948449 0.0563647 -19.424 < 2e-16 ***
DESTIN_GRID_ID1025 -6.0444976 0.1173867 -51.492 < 2e-16 ***
DESTIN_GRID_ID1033 0.0217336 0.0563449 0.386 0.699701
DESTIN_GRID_ID1034 0.2522215 0.0561840 4.489 7.15e-06 ***
DESTIN_GRID_ID1035 0.1158026 0.0562044 2.060 0.039362 *
DESTIN_GRID_ID1036 0.2623517 0.0561614 4.671 2.99e-06 ***
DESTIN_GRID_ID1037 -0.9206151 0.0563915 -16.325 < 2e-16 ***
DESTIN_GRID_ID1043 -0.5489616 0.0570945 -9.615 < 2e-16 ***
DESTIN_GRID_ID1045 -1.2763787 0.0563354 -22.657 < 2e-16 ***
DESTIN_GRID_ID1046 -0.8885829 0.0563379 -15.772 < 2e-16 ***
DESTIN_GRID_ID1053 0.6094659 0.0562044 10.844 < 2e-16 ***
DESTIN_GRID_ID1054 0.1829412 0.0562371 3.253 0.001142 **
DESTIN_GRID_ID1055 -1.1265051 0.0567496 -19.850 < 2e-16 ***
DESTIN_GRID_ID1056 -1.4877276 0.0572089 -26.005 < 2e-16 ***
DESTIN_GRID_ID1064 -3.7137530 0.1038036 -35.777 < 2e-16 ***
DESTIN_GRID_ID1066 -0.3744355 0.0561603 -6.667 2.61e-11 ***
DESTIN_GRID_ID1067 -6.1182080 0.1534556 -39.870 < 2e-16 ***
DESTIN_GRID_ID1074 -1.5405541 0.0579816 -26.570 < 2e-16 ***
DESTIN_GRID_ID1075 -0.0962122 0.0564291 -1.705 0.088193 .
DESTIN_GRID_ID1076 -0.6566237 0.0564560 -11.631 < 2e-16 ***
DESTIN_GRID_ID1077 -1.3669684 0.0569771 -23.992 < 2e-16 ***
DESTIN_GRID_ID1079 -0.3920775 0.0563190 -6.962 3.36e-12 ***
DESTIN_GRID_ID1085 -1.9441039 0.0738699 -26.318 < 2e-16 ***
DESTIN_GRID_ID1087 -1.1466382 0.0563695 -20.341 < 2e-16 ***
DESTIN_GRID_ID1088 -0.8595991 0.0563026 -15.267 < 2e-16 ***
DESTIN_GRID_ID1094 -3.1166173 0.0791514 -39.375 < 2e-16 ***
DESTIN_GRID_ID1095 -0.7381430 0.0581852 -12.686 < 2e-16 ***
DESTIN_GRID_ID1096 -0.3387809 0.0584016 -5.801 6.60e-09 ***
DESTIN_GRID_ID1097 0.3325749 0.0561509 5.923 3.16e-09 ***
DESTIN_GRID_ID1098 -2.4036909 0.0607942 -39.538 < 2e-16 ***
DESTIN_GRID_ID1099 -1.1032825 0.0566329 -19.481 < 2e-16 ***
DESTIN_GRID_ID1105 0.8688869 0.0567697 15.305 < 2e-16 ***
DESTIN_GRID_ID1106 -4.2875844 0.1102128 -38.903 < 2e-16 ***
DESTIN_GRID_ID1107 -0.7329182 0.0565363 -12.964 < 2e-16 ***
DESTIN_GRID_ID1108 1.3684800 0.0560412 24.419 < 2e-16 ***
DESTIN_GRID_ID1109 -3.6179256 0.0661126 -54.724 < 2e-16 ***
DESTIN_GRID_ID1116 -0.4899708 0.0566723 -8.646 < 2e-16 ***
DESTIN_GRID_ID1117 -0.1956696 0.0565690 -3.459 0.000542 ***
DESTIN_GRID_ID1118 -2.2026675 0.0594710 -37.038 < 2e-16 ***
DESTIN_GRID_ID1119 -1.5054907 0.0571760 -26.331 < 2e-16 ***
DESTIN_GRID_ID1120 -2.0622914 0.0591041 -34.893 < 2e-16 ***
DESTIN_GRID_ID1129 -1.7798560 0.0566303 -31.429 < 2e-16 ***
DESTIN_GRID_ID1130 -0.9900757 0.0562913 -17.588 < 2e-16 ***
DESTIN_GRID_ID1131 0.1806939 0.0563988 3.204 0.001356 **
DESTIN_GRID_ID1136 0.6165746 0.0562272 10.966 < 2e-16 ***
DESTIN_GRID_ID1138 -1.8368569 0.0593292 -30.960 < 2e-16 ***
DESTIN_GRID_ID1139 -1.0148555 0.0565405 -17.949 < 2e-16 ***
DESTIN_GRID_ID1141 -0.9891565 0.0566150 -17.472 < 2e-16 ***
DESTIN_GRID_ID1148 -2.1094629 0.0636420 -33.146 < 2e-16 ***
DESTIN_GRID_ID1149 -2.1337976 0.0577745 -36.933 < 2e-16 ***
DESTIN_GRID_ID1150 -1.7783908 0.0564765 -31.489 < 2e-16 ***
DESTIN_GRID_ID1151 -0.9630634 0.0564086 -17.073 < 2e-16 ***
DESTIN_GRID_ID1158 -1.4018234 0.0572979 -24.466 < 2e-16 ***
DESTIN_GRID_ID1159 -1.2687209 0.0568714 -22.309 < 2e-16 ***
DESTIN_GRID_ID1160 0.3395028 0.0561504 6.046 1.48e-09 ***
DESTIN_GRID_ID1171 -0.7587243 0.0563460 -13.465 < 2e-16 ***
DESTIN_GRID_ID1172 0.5490922 0.0560883 9.790 < 2e-16 ***
DESTIN_GRID_ID1173 0.1311128 0.0562462 2.331 0.019751 *
DESTIN_GRID_ID1174 -2.1162222 0.0692641 -30.553 < 2e-16 ***
DESTIN_GRID_ID1178 0.7993372 0.0561210 14.243 < 2e-16 ***
DESTIN_GRID_ID1179 -0.1569370 0.0562657 -2.789 0.005284 **
DESTIN_GRID_ID1180 -0.0445546 0.0562092 -0.793 0.427978
DESTIN_GRID_ID1181 -1.2921618 0.0567799 -22.757 < 2e-16 ***
DESTIN_GRID_ID1183 0.4436326 0.0561478 7.901 2.76e-15 ***
DESTIN_GRID_ID1190 -1.9161568 0.0617661 -31.023 < 2e-16 ***
DESTIN_GRID_ID1192 -0.7993081 0.0562830 -14.202 < 2e-16 ***
DESTIN_GRID_ID1193 -0.5416978 0.0562665 -9.627 < 2e-16 ***
DESTIN_GRID_ID1194 0.0954661 0.0563262 1.695 0.090098 .
DESTIN_GRID_ID1200 -0.5107234 0.0565618 -9.029 < 2e-16 ***
DESTIN_GRID_ID1201 -0.7861972 0.0565853 -13.894 < 2e-16 ***
DESTIN_GRID_ID1203 -0.8681320 0.0566658 -15.320 < 2e-16 ***
DESTIN_GRID_ID1204 -1.0200036 0.0567253 -17.981 < 2e-16 ***
DESTIN_GRID_ID1211 -5.9156713 0.4507525 -13.124 < 2e-16 ***
DESTIN_GRID_ID1214 -1.7415950 0.0567527 -30.687 < 2e-16 ***
DESTIN_GRID_ID1215 -0.8865057 0.0572496 -15.485 < 2e-16 ***
DESTIN_GRID_ID1216 -0.4037739 0.0568984 -7.096 1.28e-12 ***
DESTIN_GRID_ID1220 -0.3070784 0.0563738 -5.447 5.12e-08 ***
DESTIN_GRID_ID1221 0.2739762 0.0561645 4.878 1.07e-06 ***
DESTIN_GRID_ID1222 -0.9280494 0.0575813 -16.117 < 2e-16 ***
DESTIN_GRID_ID1223 -1.5900240 0.0575691 -27.619 < 2e-16 ***
DESTIN_GRID_ID1224 -0.7832623 0.0565781 -13.844 < 2e-16 ***
DESTIN_GRID_ID1231 -3.3950688 0.0847194 -40.074 < 2e-16 ***
DESTIN_GRID_ID1232 -1.3990563 0.0601363 -23.265 < 2e-16 ***
DESTIN_GRID_ID1235 -0.8428778 0.0563281 -14.964 < 2e-16 ***
DESTIN_GRID_ID1236 -0.9225098 0.0566541 -16.283 < 2e-16 ***
DESTIN_GRID_ID1241 -1.6004766 0.0574204 -27.873 < 2e-16 ***
DESTIN_GRID_ID1242 -1.1273886 0.0568413 -19.834 < 2e-16 ***
DESTIN_GRID_ID1243 0.0600661 0.0562337 1.068 0.285453
DESTIN_GRID_ID1246 -1.2647683 0.0568252 -22.257 < 2e-16 ***
DESTIN_GRID_ID1256 -1.6008330 0.0567097 -28.229 < 2e-16 ***
DESTIN_GRID_ID1257 -0.4241964 0.0563674 -7.526 5.25e-14 ***
DESTIN_GRID_ID1258 0.5598821 0.0562445 9.954 < 2e-16 ***
DESTIN_GRID_ID1262 -1.9005625 0.0579243 -32.811 < 2e-16 ***
DESTIN_GRID_ID1263 0.4495690 0.0561059 8.013 1.12e-15 ***
DESTIN_GRID_ID1264 -0.3474671 0.0565249 -6.147 7.89e-10 ***
DESTIN_GRID_ID1265 -0.4422361 0.0566182 -7.811 5.68e-15 ***
DESTIN_GRID_ID1266 -0.4149882 0.0564482 -7.352 1.96e-13 ***
DESTIN_GRID_ID1267 -2.0472886 0.0593768 -34.480 < 2e-16 ***
DESTIN_GRID_ID1272 -5.6258239 0.1312584 -42.861 < 2e-16 ***
DESTIN_GRID_ID1273 -0.4852406 0.0564755 -8.592 < 2e-16 ***
DESTIN_GRID_ID1277 -0.3195837 0.0561988 -5.687 1.30e-08 ***
DESTIN_GRID_ID1278 -0.6145865 0.0563565 -10.905 < 2e-16 ***
DESTIN_GRID_ID1283 0.8788255 0.0561064 15.664 < 2e-16 ***
DESTIN_GRID_ID1284 0.4361826 0.0561477 7.768 7.94e-15 ***
DESTIN_GRID_ID1285 0.1850767 0.0562037 3.293 0.000991 ***
DESTIN_GRID_ID1286 -0.6940891 0.0569411 -12.190 < 2e-16 ***
DESTIN_GRID_ID1289 -3.0981492 0.0690456 -44.871 < 2e-16 ***
DESTIN_GRID_ID1293 -4.6893617 0.1038025 -45.176 < 2e-16 ***
DESTIN_GRID_ID1294 -0.6425242 0.0567614 -11.320 < 2e-16 ***
DESTIN_GRID_ID1295 -3.1406094 0.0616807 -50.917 < 2e-16 ***
DESTIN_GRID_ID1298 -1.2028516 0.0564791 -21.297 < 2e-16 ***
DESTIN_GRID_ID1299 -1.4008336 0.0568000 -24.663 < 2e-16 ***
DESTIN_GRID_ID1304 -0.0713686 0.0563282 -1.267 0.205150
DESTIN_GRID_ID1305 -0.0644863 0.0561860 -1.148 0.251081
DESTIN_GRID_ID1307 -1.3079104 0.0592470 -22.076 < 2e-16 ***
DESTIN_GRID_ID1308 -0.1669355 0.0562911 -2.966 0.003021 **
DESTIN_GRID_ID1310 -5.0563677 0.2305194 -21.935 < 2e-16 ***
DESTIN_GRID_ID1316 -2.4150012 0.0582382 -41.468 < 2e-16 ***
DESTIN_GRID_ID1317 -2.6674423 0.0578448 -46.114 < 2e-16 ***
DESTIN_GRID_ID1318 -2.7409692 0.0585896 -46.783 < 2e-16 ***
DESTIN_GRID_ID1319 0.1663581 0.0561330 2.964 0.003040 **
DESTIN_GRID_ID1320 -1.7703993 0.0575429 -30.767 < 2e-16 ***
DESTIN_GRID_ID1324 -0.2540998 0.0594494 -4.274 1.92e-05 ***
DESTIN_GRID_ID1325 -2.1732162 0.0584376 -37.189 < 2e-16 ***
DESTIN_GRID_ID1326 -0.5041602 0.0563610 -8.945 < 2e-16 ***
DESTIN_GRID_ID1327 -0.2307335 0.0562796 -4.100 4.14e-05 ***
DESTIN_GRID_ID1328 -0.4262642 0.0564436 -7.552 4.28e-14 ***
DESTIN_GRID_ID1329 -0.6339154 0.0568455 -11.152 < 2e-16 ***
DESTIN_GRID_ID1330 0.7151353 0.0562343 12.717 < 2e-16 ***
DESTIN_GRID_ID1331 -5.8929992 0.2940573 -20.040 < 2e-16 ***
DESTIN_GRID_ID1333 -1.9459809 0.0585170 -33.255 < 2e-16 ***
DESTIN_GRID_ID1334 -1.6063561 0.0577820 -27.800 < 2e-16 ***
DESTIN_GRID_ID1335 0.0863873 0.0562972 1.534 0.124910
DESTIN_GRID_ID1336 -3.2089495 0.0739635 -43.386 < 2e-16 ***
DESTIN_GRID_ID1337 -3.5694714 0.0658533 -54.203 < 2e-16 ***
DESTIN_GRID_ID1338 -3.8762683 0.0630010 -61.527 < 2e-16 ***
DESTIN_GRID_ID1339 -0.2698623 0.0561597 -4.805 1.55e-06 ***
DESTIN_GRID_ID1340 -1.6412238 0.0569364 -28.826 < 2e-16 ***
DESTIN_GRID_ID1341 -5.3242659 0.1106203 -48.131 < 2e-16 ***
DESTIN_GRID_ID1346 -0.3733345 0.0565706 -6.599 4.13e-11 ***
DESTIN_GRID_ID1347 0.8264902 0.0561302 14.725 < 2e-16 ***
DESTIN_GRID_ID1348 -0.6400844 0.0564836 -11.332 < 2e-16 ***
DESTIN_GRID_ID1349 0.3608112 0.0562810 6.411 1.45e-10 ***
DESTIN_GRID_ID1350 -1.3051446 0.0577490 -22.600 < 2e-16 ***
DESTIN_GRID_ID1353 -0.6562108 0.0564851 -11.617 < 2e-16 ***
DESTIN_GRID_ID1354 -1.3310922 0.0569362 -23.379 < 2e-16 ***
DESTIN_GRID_ID1355 -1.7218429 0.0572762 -30.062 < 2e-16 ***
DESTIN_GRID_ID1357 -2.2254488 0.0593065 -37.525 < 2e-16 ***
DESTIN_GRID_ID1358 -0.1215790 0.0561424 -2.166 0.030346 *
DESTIN_GRID_ID1359 -1.4462750 0.0563800 -25.652 < 2e-16 ***
DESTIN_GRID_ID1360 -1.5842881 0.0564751 -28.053 < 2e-16 ***
DESTIN_GRID_ID1361 -1.5921459 0.0569358 -27.964 < 2e-16 ***
DESTIN_GRID_ID1362 -2.7565616 0.0627578 -43.924 < 2e-16 ***
DESTIN_GRID_ID1368 -1.3115215 0.0569378 -23.034 < 2e-16 ***
DESTIN_GRID_ID1369 -1.1163741 0.0567611 -19.668 < 2e-16 ***
DESTIN_GRID_ID1370 0.4662678 0.0561269 8.307 < 2e-16 ***
DESTIN_GRID_ID1371 -0.3716123 0.0564942 -6.578 4.77e-11 ***
DESTIN_GRID_ID1372 -0.3792344 0.0564166 -6.722 1.79e-11 ***
DESTIN_GRID_ID1373 -3.3759961 0.0665033 -50.764 < 2e-16 ***
DESTIN_GRID_ID1374 -2.1744159 0.0581932 -37.365 < 2e-16 ***
DESTIN_GRID_ID1375 -0.3492637 0.0565521 -6.176 6.58e-10 ***
DESTIN_GRID_ID1376 -1.9814195 0.0585659 -33.832 < 2e-16 ***
DESTIN_GRID_ID1379 -5.3610490 0.0957314 -56.001 < 2e-16 ***
DESTIN_GRID_ID1380 0.4124218 0.0560723 7.355 1.91e-13 ***
DESTIN_GRID_ID1381 0.6117672 0.0560605 10.913 < 2e-16 ***
DESTIN_GRID_ID1382 -0.1748660 0.0562136 -3.111 0.001866 **
DESTIN_GRID_ID1383 -2.8686210 0.0594860 -48.223 < 2e-16 ***
DESTIN_GRID_ID1388 -0.5399947 0.0564544 -9.565 < 2e-16 ***
DESTIN_GRID_ID1389 -0.7831467 0.0565800 -13.841 < 2e-16 ***
DESTIN_GRID_ID1390 -0.4369787 0.0564751 -7.738 1.01e-14 ***
DESTIN_GRID_ID1391 0.2818901 0.0562226 5.014 5.34e-07 ***
DESTIN_GRID_ID1392 -0.2892043 0.0571774 -5.058 4.24e-07 ***
DESTIN_GRID_ID1393 -0.9543594 0.0566339 -16.851 < 2e-16 ***
DESTIN_GRID_ID1394 -0.6306946 0.0563639 -11.190 < 2e-16 ***
DESTIN_GRID_ID1395 -1.0966606 0.0565314 -19.399 < 2e-16 ***
DESTIN_GRID_ID1396 -0.3486738 0.0562614 -6.197 5.74e-10 ***
DESTIN_GRID_ID1397 -1.4559847 0.0566855 -25.685 < 2e-16 ***
DESTIN_GRID_ID1398 -1.6474089 0.0578739 -28.465 < 2e-16 ***
DESTIN_GRID_ID1400 -2.2047153 0.0571070 -38.607 < 2e-16 ***
DESTIN_GRID_ID1401 0.1519269 0.0560722 2.709 0.006739 **
DESTIN_GRID_ID1402 -1.1635299 0.0562849 -20.672 < 2e-16 ***
DESTIN_GRID_ID1404 -1.8719506 0.0619283 -30.228 < 2e-16 ***
DESTIN_GRID_ID1410 0.0120130 0.0562376 0.214 0.830850
DESTIN_GRID_ID1411 -0.4089800 0.0565577 -7.231 4.79e-13 ***
DESTIN_GRID_ID1412 0.1445462 0.0561798 2.573 0.010084 *
DESTIN_GRID_ID1413 -0.5212855 0.0564085 -9.241 < 2e-16 ***
DESTIN_GRID_ID1414 -0.5686936 0.0563252 -10.097 < 2e-16 ***
DESTIN_GRID_ID1415 -0.2849805 0.0562757 -5.064 4.11e-07 ***
DESTIN_GRID_ID1416 -0.8163139 0.0564687 -14.456 < 2e-16 ***
DESTIN_GRID_ID1417 -0.6441569 0.0562683 -11.448 < 2e-16 ***
DESTIN_GRID_ID1418 -0.7519979 0.0563162 -13.353 < 2e-16 ***
DESTIN_GRID_ID1419 -1.0772327 0.0565372 -19.054 < 2e-16 ***
DESTIN_GRID_ID1422 -1.4993952 0.0563312 -26.617 < 2e-16 ***
DESTIN_GRID_ID1423 -1.0567996 0.0562568 -18.785 < 2e-16 ***
DESTIN_GRID_ID1430 0.2402810 0.0562486 4.272 1.94e-05 ***
DESTIN_GRID_ID1431 0.5128821 0.0561424 9.135 < 2e-16 ***
DESTIN_GRID_ID1432 0.2243472 0.0561564 3.995 6.47e-05 ***
DESTIN_GRID_ID1433 -0.6633415 0.0568912 -11.660 < 2e-16 ***
DESTIN_GRID_ID1434 0.3404229 0.0561568 6.062 1.34e-09 ***
DESTIN_GRID_ID1435 -0.2068336 0.0562007 -3.680 0.000233 ***
DESTIN_GRID_ID1436 -1.5213404 0.0570610 -26.662 < 2e-16 ***
DESTIN_GRID_ID1437 -0.9047478 0.0563982 -16.042 < 2e-16 ***
DESTIN_GRID_ID1438 -0.4008084 0.0561695 -7.136 9.63e-13 ***
DESTIN_GRID_ID1439 0.4142605 0.0561060 7.384 1.54e-13 ***
DESTIN_GRID_ID1440 -0.3627227 0.0564152 -6.430 1.28e-10 ***
DESTIN_GRID_ID1442 -3.4349168 0.0590845 -58.136 < 2e-16 ***
DESTIN_GRID_ID1443 -1.4803489 0.0563257 -26.282 < 2e-16 ***
DESTIN_GRID_ID1444 -0.2613278 0.0562928 -4.642 3.45e-06 ***
DESTIN_GRID_ID1452 0.9372118 0.0560835 16.711 < 2e-16 ***
DESTIN_GRID_ID1453 -0.0392101 0.0562821 -0.697 0.486008
DESTIN_GRID_ID1454 -1.0523804 0.0574853 -18.307 < 2e-16 ***
DESTIN_GRID_ID1455 -0.4181875 0.0564866 -7.403 1.33e-13 ***
DESTIN_GRID_ID1456 -0.4642474 0.0563364 -8.241 < 2e-16 ***
DESTIN_GRID_ID1457 0.0818535 0.0562064 1.456 0.145309
DESTIN_GRID_ID1458 1.0116123 0.0560517 18.048 < 2e-16 ***
DESTIN_GRID_ID1459 -1.7722109 0.0567256 -31.242 < 2e-16 ***
DESTIN_GRID_ID1460 -0.5731248 0.0561941 -10.199 < 2e-16 ***
DESTIN_GRID_ID1461 -0.6607273 0.0564388 -11.707 < 2e-16 ***
DESTIN_GRID_ID1464 -1.4871496 0.0564299 -26.354 < 2e-16 ***
DESTIN_GRID_ID1465 -2.3599949 0.0570494 -41.368 < 2e-16 ***
DESTIN_GRID_ID1472 -0.1341163 0.0565342 -2.372 0.017678 *
DESTIN_GRID_ID1473 0.7366699 0.0561210 13.126 < 2e-16 ***
DESTIN_GRID_ID1474 0.4421143 0.0561082 7.880 3.28e-15 ***
DESTIN_GRID_ID1475 0.0068956 0.0561992 0.123 0.902345
DESTIN_GRID_ID1476 -0.8317474 0.0565221 -14.715 < 2e-16 ***
DESTIN_GRID_ID1477 0.8981443 0.0560443 16.026 < 2e-16 ***
DESTIN_GRID_ID1478 -0.6799004 0.0562573 -12.086 < 2e-16 ***
DESTIN_GRID_ID1479 -1.4465018 0.0565124 -25.596 < 2e-16 ***
DESTIN_GRID_ID1480 0.7617366 0.0560509 13.590 < 2e-16 ***
DESTIN_GRID_ID1481 -0.9124089 0.0564500 -16.163 < 2e-16 ***
DESTIN_GRID_ID1482 0.3231851 0.0562173 5.749 8.98e-09 ***
DESTIN_GRID_ID1485 -2.4649947 0.0570576 -43.202 < 2e-16 ***
DESTIN_GRID_ID1494 0.5656674 0.0561646 10.072 < 2e-16 ***
DESTIN_GRID_ID1495 -0.4026790 0.0563576 -7.145 8.99e-13 ***
DESTIN_GRID_ID1496 0.4070715 0.0561175 7.254 4.05e-13 ***
DESTIN_GRID_ID1497 -0.8998554 0.0565893 -15.902 < 2e-16 ***
DESTIN_GRID_ID1498 -0.7495995 0.0564193 -13.286 < 2e-16 ***
DESTIN_GRID_ID1499 -0.4803866 0.0561922 -8.549 < 2e-16 ***
DESTIN_GRID_ID1500 -0.7756354 0.0566497 -13.692 < 2e-16 ***
DESTIN_GRID_ID1501 -0.1512214 0.0561353 -2.694 0.007063 **
DESTIN_GRID_ID1502 -0.3109246 0.0561737 -5.535 3.11e-08 ***
DESTIN_GRID_ID1506 -3.1709515 0.0885151 -35.824 < 2e-16 ***
DESTIN_GRID_ID1515 -0.3433243 0.0579436 -5.925 3.12e-09 ***
DESTIN_GRID_ID1516 0.4752986 0.0561152 8.470 < 2e-16 ***
DESTIN_GRID_ID1517 -0.3907037 0.0564551 -6.921 4.50e-12 ***
DESTIN_GRID_ID1518 -1.2320906 0.0566958 -21.732 < 2e-16 ***
DESTIN_GRID_ID1519 -1.0815821 0.0566947 -19.077 < 2e-16 ***
DESTIN_GRID_ID1520 -1.2514399 0.0564637 -22.164 < 2e-16 ***
DESTIN_GRID_ID1521 -1.1988883 0.0564997 -21.219 < 2e-16 ***
DESTIN_GRID_ID1522 -0.6073220 0.0562469 -10.797 < 2e-16 ***
DESTIN_GRID_ID1523 0.7713350 0.0561859 13.728 < 2e-16 ***
DESTIN_GRID_ID1524 -1.6558923 0.0574514 -28.823 < 2e-16 ***
DESTIN_GRID_ID1527 -4.1253127 0.0654102 -63.068 < 2e-16 ***
DESTIN_GRID_ID1535 -0.7941945 0.0907170 -8.755 < 2e-16 ***
DESTIN_GRID_ID1536 -1.8448710 0.0634234 -29.088 < 2e-16 ***
DESTIN_GRID_ID1537 0.0323050 0.0563670 0.573 0.566564
DESTIN_GRID_ID1538 -0.2481437 0.0562784 -4.409 1.04e-05 ***
DESTIN_GRID_ID1539 -0.2643649 0.0562073 -4.703 2.56e-06 ***
DESTIN_GRID_ID1540 -0.9885820 0.0563679 -17.538 < 2e-16 ***
DESTIN_GRID_ID1541 -0.2239269 0.0565697 -3.958 7.54e-05 ***
DESTIN_GRID_ID1542 -0.9796303 0.0567708 -17.256 < 2e-16 ***
DESTIN_GRID_ID1543 -1.4382774 0.0631167 -22.788 < 2e-16 ***
DESTIN_GRID_ID1544 -1.2251270 0.0568350 -21.556 < 2e-16 ***
DESTIN_GRID_ID1547 -1.8100001 0.0577965 -31.317 < 2e-16 ***
DESTIN_GRID_ID1556 -0.8163525 0.0924550 -8.830 < 2e-16 ***
DESTIN_GRID_ID1557 -1.4761208 0.0599492 -24.623 < 2e-16 ***
DESTIN_GRID_ID1558 -0.3636404 0.0576838 -6.304 2.90e-10 ***
DESTIN_GRID_ID1559 0.2742307 0.0561391 4.885 1.04e-06 ***
DESTIN_GRID_ID1560 0.2784745 0.0561241 4.962 6.99e-07 ***
DESTIN_GRID_ID1561 -0.6254181 0.0564411 -11.081 < 2e-16 ***
DESTIN_GRID_ID1562 -2.5702562 0.0584793 -43.952 < 2e-16 ***
DESTIN_GRID_ID1563 -1.7619780 0.0568608 -30.988 < 2e-16 ***
DESTIN_GRID_ID1564 -1.3663327 0.0566412 -24.123 < 2e-16 ***
DESTIN_GRID_ID1565 -0.7743228 0.0563602 -13.739 < 2e-16 ***
DESTIN_GRID_ID1566 -2.5526095 0.0585160 -43.622 < 2e-16 ***
DESTIN_GRID_ID1567 -2.3618751 0.0587018 -40.235 < 2e-16 ***
DESTIN_GRID_ID1568 -1.3141941 0.0570624 -23.031 < 2e-16 ***
DESTIN_GRID_ID1578 -1.3190708 0.1247770 -10.571 < 2e-16 ***
DESTIN_GRID_ID1580 -2.6108091 0.0633109 -41.238 < 2e-16 ***
DESTIN_GRID_ID1581 -0.1850103 0.0562216 -3.291 0.000999 ***
DESTIN_GRID_ID1582 0.0424851 0.0561310 0.757 0.449115
DESTIN_GRID_ID1583 -1.9273901 0.0602864 -31.971 < 2e-16 ***
DESTIN_GRID_ID1584 -1.6439189 0.0574286 -28.625 < 2e-16 ***
DESTIN_GRID_ID1585 -1.3118057 0.0567277 -23.125 < 2e-16 ***
DESTIN_GRID_ID1586 -0.4969281 0.0562620 -8.832 < 2e-16 ***
DESTIN_GRID_ID1589 -2.7560342 0.0601088 -45.851 < 2e-16 ***
DESTIN_GRID_ID1590 -1.5568843 0.0575746 -27.041 < 2e-16 ***
DESTIN_GRID_ID1600 -0.7503911 0.0583714 -12.855 < 2e-16 ***
DESTIN_GRID_ID1601 -1.1178491 0.0565223 -19.777 < 2e-16 ***
DESTIN_GRID_ID1602 -0.7797042 0.0564628 -13.809 < 2e-16 ***
DESTIN_GRID_ID1603 0.3455114 0.0561370 6.155 7.52e-10 ***
DESTIN_GRID_ID1604 -1.9364574 0.0571300 -33.896 < 2e-16 ***
DESTIN_GRID_ID1605 -0.8954749 0.0563202 -15.900 < 2e-16 ***
DESTIN_GRID_ID1606 -1.7387458 0.0580666 -29.944 < 2e-16 ***
DESTIN_GRID_ID1607 -0.3146466 0.0561603 -5.603 2.11e-08 ***
DESTIN_GRID_ID1608 -1.1639125 0.0564078 -20.634 < 2e-16 ***
DESTIN_GRID_ID1609 -0.3933558 0.0562390 -6.994 2.66e-12 ***
DESTIN_GRID_ID1610 -2.5333015 0.0625813 -40.480 < 2e-16 ***
DESTIN_GRID_ID1622 -0.5042262 0.0574507 -8.777 < 2e-16 ***
DESTIN_GRID_ID1623 -0.0752178 0.0561612 -1.339 0.180466
DESTIN_GRID_ID1624 0.4856120 0.0561281 8.652 < 2e-16 ***
DESTIN_GRID_ID1625 -0.4353138 0.0563043 -7.731 1.06e-14 ***
DESTIN_GRID_ID1626 1.2366502 0.0560353 22.069 < 2e-16 ***
DESTIN_GRID_ID1627 -1.8594917 0.0567623 -32.759 < 2e-16 ***
DESTIN_GRID_ID1628 0.1682392 0.0561128 2.998 0.002716 **
DESTIN_GRID_ID1629 -2.8924365 0.0582083 -49.691 < 2e-16 ***
DESTIN_GRID_ID1630 -2.4213773 0.0572683 -42.281 < 2e-16 ***
DESTIN_GRID_ID1631 -2.6722153 0.0587589 -45.478 < 2e-16 ***
DESTIN_GRID_ID1642 -2.8182690 0.0654096 -43.086 < 2e-16 ***
DESTIN_GRID_ID1643 -0.5641668 0.0563260 -10.016 < 2e-16 ***
DESTIN_GRID_ID1644 -0.5549800 0.0565921 -9.807 < 2e-16 ***
DESTIN_GRID_ID1645 -0.7288619 0.0563907 -12.925 < 2e-16 ***
DESTIN_GRID_ID1646 -0.4377193 0.0565836 -7.736 1.03e-14 ***
DESTIN_GRID_ID1647 -1.2150551 0.0563745 -21.553 < 2e-16 ***
DESTIN_GRID_ID1648 -1.0752328 0.0562973 -19.099 < 2e-16 ***
DESTIN_GRID_ID1649 -0.5287483 0.0561570 -9.416 < 2e-16 ***
DESTIN_GRID_ID1650 -1.4871398 0.0565559 -26.295 < 2e-16 ***
DESTIN_GRID_ID1664 -5.0255557 0.1428154 -35.189 < 2e-16 ***
DESTIN_GRID_ID1665 0.0371359 0.0561477 0.661 0.508358
DESTIN_GRID_ID1666 0.0796769 0.0561418 1.419 0.155838
DESTIN_GRID_ID1667 -0.6318587 0.0578889 -10.915 < 2e-16 ***
DESTIN_GRID_ID1668 -1.1994504 0.0564632 -21.243 < 2e-16 ***
DESTIN_GRID_ID1670 -0.7036513 0.0561807 -12.525 < 2e-16 ***
DESTIN_GRID_ID1671 -1.2830001 0.0573073 -22.388 < 2e-16 ***
DESTIN_GRID_ID1672 -2.2143666 0.0574212 -38.564 < 2e-16 ***
DESTIN_GRID_ID1684 -0.2317098 0.0567499 -4.083 4.45e-05 ***
DESTIN_GRID_ID1685 -1.4716794 0.0568459 -25.889 < 2e-16 ***
DESTIN_GRID_ID1686 -0.5813428 0.0563005 -10.326 < 2e-16 ***
DESTIN_GRID_ID1687 -0.3231696 0.0564314 -5.727 1.02e-08 ***
DESTIN_GRID_ID1688 -1.1312113 0.0564621 -20.035 < 2e-16 ***
DESTIN_GRID_ID1689 -1.8906292 0.0569714 -33.186 < 2e-16 ***
DESTIN_GRID_ID1690 -2.5820784 0.0577036 -44.747 < 2e-16 ***
DESTIN_GRID_ID1691 -0.6092330 0.0561720 -10.846 < 2e-16 ***
DESTIN_GRID_ID1692 -2.7004287 0.0580717 -46.502 < 2e-16 ***
DESTIN_GRID_ID1706 -0.7000046 0.0565850 -12.371 < 2e-16 ***
DESTIN_GRID_ID1707 -1.4942535 0.0566929 -26.357 < 2e-16 ***
DESTIN_GRID_ID1708 -0.8983187 0.0564037 -15.927 < 2e-16 ***
DESTIN_GRID_ID1709 -0.1412104 0.0561910 -2.513 0.011969 *
DESTIN_GRID_ID1710 -0.3192656 0.0562213 -5.679 1.36e-08 ***
DESTIN_GRID_ID1711 0.1406878 0.0561128 2.507 0.012168 *
DESTIN_GRID_ID1712 -0.7738740 0.0561849 -13.774 < 2e-16 ***
DESTIN_GRID_ID1713 -3.1477964 0.0584364 -53.867 < 2e-16 ***
DESTIN_GRID_ID1714 -1.8226498 0.0567094 -32.140 < 2e-16 ***
DESTIN_GRID_ID1727 -0.2172339 0.0562909 -3.859 0.000114 ***
DESTIN_GRID_ID1728 -0.1968093 0.0561894 -3.503 0.000461 ***
DESTIN_GRID_ID1729 -0.0867458 0.0561659 -1.544 0.122477
DESTIN_GRID_ID1730 -1.0552543 0.0566161 -18.639 < 2e-16 ***
DESTIN_GRID_ID1731 -0.2473077 0.0561798 -4.402 1.07e-05 ***
DESTIN_GRID_ID1732 -0.9305739 0.0562220 -16.552 < 2e-16 ***
DESTIN_GRID_ID1733 -2.0976627 0.0566967 -36.998 < 2e-16 ***
DESTIN_GRID_ID1734 -0.8859886 0.0562164 -15.760 < 2e-16 ***
DESTIN_GRID_ID1735 -1.7385951 0.0583489 -29.797 < 2e-16 ***
DESTIN_GRID_ID1748 -1.2600845 0.0568283 -22.174 < 2e-16 ***
DESTIN_GRID_ID1749 -0.0639011 0.0561507 -1.138 0.255108
DESTIN_GRID_ID1750 -0.0802042 0.0561624 -1.428 0.153270
DESTIN_GRID_ID1751 -0.5259593 0.0563560 -9.333 < 2e-16 ***
DESTIN_GRID_ID1753 -0.3522803 0.0561785 -6.271 3.59e-10 ***
DESTIN_GRID_ID1754 0.4846278 0.0560551 8.646 < 2e-16 ***
DESTIN_GRID_ID1755 -0.3103366 0.0561101 -5.531 3.19e-08 ***
DESTIN_GRID_ID1756 -1.3568084 0.0563020 -24.099 < 2e-16 ***
DESTIN_GRID_ID1757 -3.6737329 0.0606533 -60.569 < 2e-16 ***
DESTIN_GRID_ID1769 -0.5256110 0.0563428 -9.329 < 2e-16 ***
DESTIN_GRID_ID1770 -0.7938658 0.0566404 -14.016 < 2e-16 ***
DESTIN_GRID_ID1771 0.0070639 0.0562401 0.126 0.900047
DESTIN_GRID_ID1772 1.1115614 0.0564604 19.687 < 2e-16 ***
DESTIN_GRID_ID1774 -1.5082504 0.0564625 -26.712 < 2e-16 ***
DESTIN_GRID_ID1775 -1.9289768 0.0565779 -34.094 < 2e-16 ***
DESTIN_GRID_ID1776 0.2599404 0.0560642 4.636 3.54e-06 ***
DESTIN_GRID_ID1777 -1.8826943 0.0565413 -33.298 < 2e-16 ***
DESTIN_GRID_ID1778 -2.8377050 0.0605474 -46.867 < 2e-16 ***
DESTIN_GRID_ID1790 0.0072355 0.0562594 0.129 0.897666
DESTIN_GRID_ID1791 -0.6542492 0.0563978 -11.601 < 2e-16 ***
DESTIN_GRID_ID1792 -0.3670789 0.0564863 -6.499 8.11e-11 ***
DESTIN_GRID_ID1793 -0.3762023 0.0563042 -6.682 2.36e-11 ***
DESTIN_GRID_ID1794 1.4224407 0.0564997 25.176 < 2e-16 ***
DESTIN_GRID_ID1795 -2.8326853 0.0599599 -47.243 < 2e-16 ***
DESTIN_GRID_ID1796 -0.8397113 0.0562573 -14.926 < 2e-16 ***
DESTIN_GRID_ID1797 -1.2642623 0.0562844 -22.462 < 2e-16 ***
DESTIN_GRID_ID1798 -1.1878587 0.0562565 -21.115 < 2e-16 ***
DESTIN_GRID_ID1799 -2.1283112 0.0568006 -37.470 < 2e-16 ***
DESTIN_GRID_ID1800 -4.2520656 0.0860342 -49.423 < 2e-16 ***
DESTIN_GRID_ID1811 -1.0307687 0.0566774 -18.187 < 2e-16 ***
DESTIN_GRID_ID1812 0.4061074 0.0560944 7.240 4.50e-13 ***
DESTIN_GRID_ID1813 0.6414231 0.0560821 11.437 < 2e-16 ***
DESTIN_GRID_ID1817 -2.6763341 0.0577251 -46.363 < 2e-16 ***
DESTIN_GRID_ID1818 -1.5757006 0.0563199 -27.978 < 2e-16 ***
DESTIN_GRID_ID1819 0.0959813 0.0560782 1.712 0.086978 .
DESTIN_GRID_ID1820 -4.5931976 0.0758049 -60.592 < 2e-16 ***
DESTIN_GRID_ID1832 0.1819145 0.0561923 3.237 0.001206 **
DESTIN_GRID_ID1833 -1.0710083 0.0565055 -18.954 < 2e-16 ***
DESTIN_GRID_ID1834 -1.0530562 0.0564272 -18.662 < 2e-16 ***
DESTIN_GRID_ID1835 -0.9629529 0.0565330 -17.033 < 2e-16 ***
DESTIN_GRID_ID1837 -1.0999901 0.0577578 -19.045 < 2e-16 ***
DESTIN_GRID_ID1839 -2.7380532 0.0576328 -47.509 < 2e-16 ***
DESTIN_GRID_ID1840 0.1609742 0.0560890 2.870 0.004105 **
DESTIN_GRID_ID1841 -3.7373920 0.0627607 -59.550 < 2e-16 ***
DESTIN_GRID_ID1842 -1.2239306 0.0589012 -20.779 < 2e-16 ***
DESTIN_GRID_ID1853 -0.5572207 0.0563105 -9.896 < 2e-16 ***
DESTIN_GRID_ID1854 -0.3941814 0.0562575 -7.007 2.44e-12 ***
DESTIN_GRID_ID1855 0.0031270 0.0561873 0.056 0.955619
DESTIN_GRID_ID1858 0.0653600 0.0566232 1.154 0.248378
DESTIN_GRID_ID1860 -2.0995796 0.0602267 -34.861 < 2e-16 ***
DESTIN_GRID_ID1861 -1.3525518 0.0563361 -24.009 < 2e-16 ***
DESTIN_GRID_ID1874 -1.0620442 0.0569911 -18.635 < 2e-16 ***
DESTIN_GRID_ID1875 -2.8331604 0.0608755 -46.540 < 2e-16 ***
DESTIN_GRID_ID1876 -1.5049449 0.0612418 -24.574 < 2e-16 ***
DESTIN_GRID_ID1877 -0.2091313 0.0562248 -3.720 0.000200 ***
DESTIN_GRID_ID1880 -0.8612436 0.0577663 -14.909 < 2e-16 ***
DESTIN_GRID_ID1882 -1.4500952 0.0563903 -25.715 < 2e-16 ***
DESTIN_GRID_ID1883 -2.5748773 0.0600861 -42.853 < 2e-16 ***
DESTIN_GRID_ID1895 -0.0928986 0.0562300 -1.652 0.098510 .
DESTIN_GRID_ID1896 -1.2265026 0.0565805 -21.677 < 2e-16 ***
DESTIN_GRID_ID1897 -2.0580997 0.0575054 -35.790 < 2e-16 ***
DESTIN_GRID_ID1898 -2.4026504 0.0615818 -39.016 < 2e-16 ***
DESTIN_GRID_ID1901 -1.3869945 0.0596216 -23.263 < 2e-16 ***
DESTIN_GRID_ID1903 -3.0085122 0.0592687 -50.761 < 2e-16 ***
DESTIN_GRID_ID1917 -1.4355071 0.0568542 -25.249 < 2e-16 ***
DESTIN_GRID_ID1918 -0.2158114 0.0564160 -3.825 0.000131 ***
DESTIN_GRID_ID1919 -0.0924248 0.0562028 -1.644 0.100075
DESTIN_GRID_ID1922 -0.1571717 0.0570016 -2.757 0.005828 **
DESTIN_GRID_ID1924 -3.2507968 0.0608919 -53.386 < 2e-16 ***
DESTIN_GRID_ID1937 -0.7480455 0.0565444 -13.229 < 2e-16 ***
DESTIN_GRID_ID1938 0.0050325 0.0561854 0.090 0.928629
DESTIN_GRID_ID1939 -1.2777576 0.0567782 -22.504 < 2e-16 ***
DESTIN_GRID_ID1942 -1.5110940 0.0591827 -25.533 < 2e-16 ***
DESTIN_GRID_ID1959 -1.2446671 0.0569321 -21.862 < 2e-16 ***
DESTIN_GRID_ID1960 1.1072137 0.0560439 19.756 < 2e-16 ***
DESTIN_GRID_ID1961 -1.4005788 0.0569151 -24.608 < 2e-16 ***
DESTIN_GRID_ID1962 -0.5853418 0.0563422 -10.389 < 2e-16 ***
DESTIN_GRID_ID1964 0.1268603 0.0571511 2.220 0.026437 *
DESTIN_GRID_ID1979 -0.7155644 0.0566370 -12.634 < 2e-16 ***
DESTIN_GRID_ID1980 -1.0208871 0.0564448 -18.086 < 2e-16 ***
DESTIN_GRID_ID1981 -1.0709052 0.0565011 -18.954 < 2e-16 ***
DESTIN_GRID_ID1982 -0.5799958 0.0565681 -10.253 < 2e-16 ***
DESTIN_GRID_ID1983 -0.7245608 0.0563593 -12.856 < 2e-16 ***
DESTIN_GRID_ID1984 -0.5496155 0.0563431 -9.755 < 2e-16 ***
DESTIN_GRID_ID1985 -0.4269760 0.0563014 -7.584 3.36e-14 ***
DESTIN_GRID_ID2001 -0.7346331 0.0564230 -13.020 < 2e-16 ***
DESTIN_GRID_ID2002 -0.7342744 0.0562694 -13.049 < 2e-16 ***
DESTIN_GRID_ID2003 -0.0732747 0.0561773 -1.304 0.192115
DESTIN_GRID_ID2004 0.0848614 0.0561685 1.511 0.130830
DESTIN_GRID_ID2005 -0.9063586 0.0564095 -16.067 < 2e-16 ***
DESTIN_GRID_ID2006 0.0034776 0.0562006 0.062 0.950659
DESTIN_GRID_ID2007 -3.4292222 0.0650371 -52.727 < 2e-16 ***
DESTIN_GRID_ID2022 -0.2185046 0.0564231 -3.873 0.000108 ***
DESTIN_GRID_ID2023 -0.2161546 0.0562044 -3.846 0.000120 ***
DESTIN_GRID_ID2024 0.1103676 0.0561345 1.966 0.049284 *
DESTIN_GRID_ID2025 -1.2961431 0.0564540 -22.959 < 2e-16 ***
DESTIN_GRID_ID2026 -1.9602790 0.0574415 -34.127 < 2e-16 ***
DESTIN_GRID_ID2027 0.1040113 0.0561703 1.852 0.064067 .
DESTIN_GRID_ID2043 -1.6723905 0.0573765 -29.148 < 2e-16 ***
DESTIN_GRID_ID2044 -0.7190239 0.0563398 -12.762 < 2e-16 ***
DESTIN_GRID_ID2045 -1.3242771 0.0573657 -23.085 < 2e-16 ***
DESTIN_GRID_ID2046 0.0307629 0.0561202 0.548 0.583581
DESTIN_GRID_ID2047 -1.8904990 0.0569321 -33.206 < 2e-16 ***
DESTIN_GRID_ID2048 -1.5992423 0.0567696 -28.171 < 2e-16 ***
DESTIN_GRID_ID2049 -3.3435477 0.0636993 -52.490 < 2e-16 ***
DESTIN_GRID_ID2064 -0.8331992 0.0564961 -14.748 < 2e-16 ***
DESTIN_GRID_ID2065 -0.9603725 0.0564874 -17.002 < 2e-16 ***
DESTIN_GRID_ID2066 -3.3017117 0.0676825 -48.782 < 2e-16 ***
DESTIN_GRID_ID2067 1.5771048 0.0560328 28.146 < 2e-16 ***
DESTIN_GRID_ID2068 -1.9801810 0.0580675 -34.101 < 2e-16 ***
DESTIN_GRID_ID2069 -1.4197393 0.0567743 -25.007 < 2e-16 ***
DESTIN_GRID_ID2085 -0.6410314 0.0565083 -11.344 < 2e-16 ***
DESTIN_GRID_ID2086 0.6718152 0.0561245 11.970 < 2e-16 ***
DESTIN_GRID_ID2087 0.3628593 0.0561419 6.463 1.02e-10 ***
DESTIN_GRID_ID2088 -0.8941529 0.0563189 -15.877 < 2e-16 ***
DESTIN_GRID_ID2089 -1.3685561 0.0567848 -24.101 < 2e-16 ***
DESTIN_GRID_ID2090 1.2715583 0.0560524 22.685 < 2e-16 ***
DESTIN_GRID_ID2091 -4.1213468 0.0905414 -45.519 < 2e-16 ***
DESTIN_GRID_ID2105 -1.5023249 0.0870253 -17.263 < 2e-16 ***
DESTIN_GRID_ID2106 -2.1815299 0.0581565 -37.511 < 2e-16 ***
DESTIN_GRID_ID2107 0.5416533 0.0561264 9.651 < 2e-16 ***
DESTIN_GRID_ID2108 0.1405072 0.0562089 2.500 0.012429 *
DESTIN_GRID_ID2109 -1.3334358 0.0564647 -23.615 < 2e-16 ***
DESTIN_GRID_ID2110 -1.9963094 0.0573875 -34.786 < 2e-16 ***
DESTIN_GRID_ID2111 -3.1634481 0.0667264 -47.409 < 2e-16 ***
DESTIN_GRID_ID2128 -0.4388790 0.0566518 -7.747 9.41e-15 ***
DESTIN_GRID_ID2129 -0.7709748 0.0570881 -13.505 < 2e-16 ***
DESTIN_GRID_ID2130 -0.7328254 0.0562981 -13.017 < 2e-16 ***
DESTIN_GRID_ID2131 -0.7657533 0.0565329 -13.545 < 2e-16 ***
DESTIN_GRID_ID2132 -1.3443739 0.0566299 -23.740 < 2e-16 ***
DESTIN_GRID_ID2148 -1.3726274 0.0584860 -23.469 < 2e-16 ***
DESTIN_GRID_ID2149 -1.3268754 0.0571867 -23.203 < 2e-16 ***
DESTIN_GRID_ID2150 -1.1302668 0.0567843 -19.905 < 2e-16 ***
DESTIN_GRID_ID2151 0.7018120 0.0560814 12.514 < 2e-16 ***
DESTIN_GRID_ID2152 -0.3507991 0.0562719 -6.234 4.55e-10 ***
DESTIN_GRID_ID2153 -1.6352694 0.0573774 -28.500 < 2e-16 ***
DESTIN_GRID_ID2171 -0.1412275 0.0563115 -2.508 0.012143 *
DESTIN_GRID_ID2172 -1.7911603 0.0573140 -31.252 < 2e-16 ***
DESTIN_GRID_ID2173 -1.3366971 0.0565396 -23.642 < 2e-16 ***
DESTIN_GRID_ID2174 -0.6372229 0.0564153 -11.295 < 2e-16 ***
DESTIN_GRID_ID2191 0.0551105 0.0566394 0.973 0.330550
DESTIN_GRID_ID2192 -1.1553484 0.0571755 -20.207 < 2e-16 ***
DESTIN_GRID_ID2193 -0.4637949 0.0563862 -8.225 < 2e-16 ***
DESTIN_GRID_ID2194 -0.5562413 0.0563192 -9.877 < 2e-16 ***
DESTIN_GRID_ID2195 -2.6107074 0.0695566 -37.534 < 2e-16 ***
DESTIN_GRID_ID2212 0.4113642 0.0577887 7.118 1.09e-12 ***
DESTIN_GRID_ID2213 -0.2537901 0.0567465 -4.472 7.74e-06 ***
DESTIN_GRID_ID2214 0.6493101 0.0565131 11.490 < 2e-16 ***
DESTIN_GRID_ID2215 -1.1598872 0.0569502 -20.367 < 2e-16 ***
DESTIN_GRID_ID2216 -0.2142595 0.0563365 -3.803 0.000143 ***
DESTIN_GRID_ID2233 0.5621164 0.0569671 9.867 < 2e-16 ***
DESTIN_GRID_ID2234 1.1730833 0.0566603 20.704 < 2e-16 ***
DESTIN_GRID_ID2235 -0.2123875 0.0568083 -3.739 0.000185 ***
DESTIN_GRID_ID2236 -1.6630181 0.0577448 -28.799 < 2e-16 ***
DESTIN_GRID_ID2237 -0.1358417 0.0572497 -2.373 0.017654 *
DESTIN_GRID_ID2256 0.0331642 0.0574696 0.577 0.563889
DESTIN_GRID_ID2257 -2.5294169 0.0633023 -39.958 < 2e-16 ***
DESTIN_GRID_ID2258 -0.3925734 0.0564929 -6.949 3.68e-12 ***
DESTIN_GRID_ID2259 0.6485641 0.0570170 11.375 < 2e-16 ***
DESTIN_GRID_ID2277 -1.1966730 0.0620197 -19.295 < 2e-16 ***
DESTIN_GRID_ID2278 -1.0268498 0.0586766 -17.500 < 2e-16 ***
DESTIN_GRID_ID2279 -0.2014522 0.0565159 -3.565 0.000365 ***
DESTIN_GRID_ID2280 -1.5470825 0.0658158 -23.506 < 2e-16 ***
DESTIN_GRID_ID2297 -1.5065060 0.0597677 -25.206 < 2e-16 ***
DESTIN_GRID_ID2300 -1.1901258 0.0598384 -19.889 < 2e-16 ***
DESTIN_GRID_ID2301 -0.5003776 0.0569120 -8.792 < 2e-16 ***
DESTIN_GRID_ID2318 0.8682501 0.0562910 15.424 < 2e-16 ***
DESTIN_GRID_ID2319 0.7974185 0.0562770 14.170 < 2e-16 ***
DESTIN_GRID_ID2322 -0.2189523 0.0569049 -3.848 0.000119 ***
DESTIN_GRID_ID2337 0.1830786 0.0597480 3.064 0.002183 **
DESTIN_GRID_ID2341 1.0193345 0.0562638 18.117 < 2e-16 ***
DESTIN_GRID_ID2343 -1.0815365 0.0577954 -18.713 < 2e-16 ***
DESTIN_GRID_ID2361 -0.2374611 0.0568735 -4.175 2.98e-05 ***
DESTIN_GRID_ID2364 -2.3093525 0.0667963 -34.573 < 2e-16 ***
DESTIN_GRID_ID2379 -1.0374388 0.0630924 -16.443 < 2e-16 ***
DESTIN_GRID_ID2384 0.8574280 0.0564249 15.196 < 2e-16 ***
DESTIN_GRID_ID2405 1.6305276 0.0562193 29.003 < 2e-16 ***
DESTIN_GRID_ID2406 -1.4017293 0.0610451 -22.962 < 2e-16 ***
DESTIN_GRID_ID2426 1.0541858 0.0571471 18.447 < 2e-16 ***
DESTIN_GRID_ID2427 1.3201788 0.0564292 23.395 < 2e-16 ***
DESTIN_GRID_ID2505 0.7744157 0.0596910 12.974 < 2e-16 ***
log(dist) -1.5811965 0.0003203 -4936.306 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 82068169 on 62185 degrees of freedom
Residual deviance: 20981911 on 60551 degrees of freedom
AIC: 21321285
Number of Fisher Scoring iterations: 10Model Comparison
In this section we will use the compare_performance() of performance package to compare the root mean square error of the four SIMs. The smaller the values of RMSE , the better the model.
First of all, let us create a list called model_list by using the code chunk below. It contains all our fitted models for all four variations of gravity model.
The output below reveals that doubly constrained SIM is the best model among all the four SIMs because it has the smallest RMSE value of 1039.
Visualising the fitted values
The function below will save the fitted values as a dataframe and append that column of fitted values to the flow_data1 df. We will append all the fitted values of all the four SIMs.
flow_data1 <- process_fitted_values(flow_data1, uncSIM$fitted.values, "uncTRIPS")
flow_data1 <- process_fitted_values(flow_data1, orcSIM$fitted.values, "orcTRIPS")
flow_data1 <- process_fitted_values(flow_data1, decSIM$fitted.values, "decTRIPS")
flow_data1 <- process_fitted_values(flow_data1, dbcSIM$fitted.values, "dbcTRIPS")Using the ggarragne() function of the ggpurpackage, we will now print the ‘actual vs predicted’ plots side-by-side.
Show the code
unc_p <- ggplot(data = flow_data1,
aes(x = uncTRIPS,
y = TRIPS)) +
geom_point(size = 0.5) +
geom_smooth(method = lm)
orc_p <- ggplot(data = flow_data1,
aes(x = orcTRIPS,
y = TRIPS)) +
geom_point(size = 0.5) +
geom_smooth(method = lm)
dec_p <- ggplot(data = flow_data1,
aes(x = decTRIPS,
y = TRIPS)) +
geom_point(size = 0.5) +
geom_smooth(method = lm)
dbc_p <- ggplot(data = flow_data1,
aes(x = dbcTRIPS,
y = TRIPS)) +
geom_point(size = 0.5) +
geom_smooth(method = lm)
ggarrange(unc_p, orc_p, dec_p, dbc_p,
ncol = 2,
nrow = 2)
Discussion:
We can see that the points ‘hug’ more closely to the diagonal blue line, which indicates that doubly constrained model is indeed the best model. However, the origin constrained model is more useful in explaining the predictors that affects the flow of bus trips.
We focus our attention on the most influential factor affecting bus trips, that is count of MRT stations with the highest coefficient of 0.49. Given that I have prepared a MRT train flow data (in another exercise out of personal interest), we could incorporate this dataset into this exercise to visualise how commuters from various residential zones would potentially take bus to MRT stations.
In the map below, only bus trips above 13,000 and MRT trips above 14,800 trips are displayed. The lines represent bus flows while the pink lines represent MRT flows.
Show the code
tmap_mode('view')
tmap_options(check.and.fix = TRUE)
filtered_flowLine_bus <- flowLine %>%
filter(TRIPS >= 13000)
filtered_flowLine_train <- flowLine_train_wkdaymorn %>%
filter(TRIPS >= 14800)
bs_count_filtered <- bs_count %>%
filter(grid_id %in% c(filtered_flowLine_bus$ORIGIN_GRID_ID, filtered_flowLine_bus$DESTIN_GRID_ID))
tm_shape(mpsz) +
tm_polygons(alpha=0.7,
col='black') +
tm_shape(bs_count_filtered) +
tm_polygons(alpha=0.3) +
#tm_shape(busstop_hex_geo) +
#tm_dots(size= 0.005)+
filtered_flowLine_bus %>%
tm_shape() +
tm_lines(lwd= 'TRIPS',
scale= c(4,5,6,7,8,9),
#scale= c(2,3,4,5,6,7),
n = 6,
alpha= 0.3,
popup.vars=c("# Trips:"="TRIPS",
"Orig Desc:"="ORIGIN_DESC",
"Destin Desc:" = "DESTIN_DESC",
"Distance:" = 'dist'),
col= 'yellow') +
filtered_flowLine_train %>%
tm_shape() +
tm_lines(lwd = 'TRIPS',
style = 'quantile',
scale= c(4,5,6,7,8,9),
#scale=c(2,3,4,5,6,7),
#scale= c(0.3, 3, 9, 15, 21, 30),
#scale= c(0.1, 1, 3, 5, 7,10),
n = 6,
alpha= 0.3,
popup.vars=c("# Trips:"="TRIPS",
"Orig Desc:"="ORIGIN_DESC",
"Destin Desc:" = "DESTIN_DESC",
"Distance:" = 'dist'),
col='pink') +
tm_view(set.zoom.limits = c(11,17)) +
tm_layout(main.title = 'O-D Flow On Weekday Morning Peak hour' ,
main.title.size = 1.0,
main.title.fontface = 'bold')The map above shows how the passengers commute from their residential areas to MRT stations via the yellow lines (Bus) and then from MRT to their final destinations via the pink lines (Train).
Visualising the residual errors
There are many types of residuals in glm() models like Response, Working, Pearson, Deviance residuals for instance. For simplicity, we will work with Response type, which is derived from ‘actual’ - ‘predicted’ values. In this exercise, I would like to calculate ‘Predicted - Actual’ values instead; so that any over-prediction has positive values and under-predicted values will have a negative residual.
We will use the same function written previously to save the residual values as a dataframe and append that column of residual values to the flow_data1 df. We will append all the residual values of all the four SIMs. (If you are confused, the function name should have been changed to process_residual_values instead)
flow_data1 <- process_fitted_values(flow_data1, -resid(uncSIM, type='response'), "uncRES")
flow_data1 <- process_fitted_values(flow_data1, -resid(orcSIM, type='response'), "orcRES")
flow_data1 <- process_fitted_values(flow_data1, -resid(decSIM, type='response'), "decRES")
flow_data1 <- process_fitted_values(flow_data1, -resid(dbcSIM, type='response'), "dbcRES")
flow_data1 <- process_fitted_values(flow_data1, -resid(uncSIM, type='working'), "uncRES_norm")
flow_data1 <- process_fitted_values(flow_data1, -resid(orcSIM, type='working'), "orcRES_norm")
flow_data1 <- process_fitted_values(flow_data1, -resid(decSIM, type='working'), "decRES_norm")
flow_data1 <- process_fitted_values(flow_data1, -resid(dbcSIM, type='working'), "dbcRES_norm")Save flow_data1 to local.
Convert flow_data1 to a sf Linestring object.
flowLine2 to get a left join with od_data1 in order to append the origin and destination bus stop descriptions for our map’s tooltip function later.
Save flowLine2 to local
Reload flowLine2 into R
Plot of Residuals against Fitted Values
The charts below allow us to compare the residuals of the four models.
Show the code
unc_rf <- ggplot(data = flow_data1,
aes(x = uncTRIPS,
y = uncRES)) +
geom_point(size = 0.5) +
geom_hline(yintercept = 0, linetype = "dashed", color = "blue")
orc_rf <- ggplot(data = flow_data1,
aes(x = orcTRIPS,
y = orcRES)) +
geom_point(size = 0.5) +
geom_hline(yintercept = 0, linetype = "dashed", color = "blue")
dec_rf <- ggplot(data = flow_data1,
aes(x = decTRIPS,
y = decRES)) +
geom_point(size = 0.5) +
geom_hline(yintercept = 0, linetype = "dashed", color = "blue")
dbc_rf <- ggplot(data = flow_data1,
aes(x = dbcTRIPS,
y = dbcRES)) +
geom_point(size = 0.5) +
geom_hline(yintercept = 0, linetype = "dashed", color = "blue")
ggarrange(unc_rf, orc_rf, dec_rf, dbc_rf,
ncol = 2,
nrow = 2)
All four models produces under-predicted (below X-axis) and over-predicted above X-axis) values. The unconstrained and origin-constrained model (top left) produces greater magnitude of under-predicted errors . The maximum number of actual trips is 75,364 and yet the unconstrained model produces only a maximum of about 15k trips.
Coordinated Plot: Residuals against Fitted Values
Using the highlight() and subplot() functions of the plotly package, we print the ‘residual vs predicted’ coordinated plots side-by-side. Clicking on any point in one of the chart will highlight the same point in the other three maps.
Since the best model is doubly-constrained, we filter to retain only the data points with over-predicted trips of above 20,000 and under-predicted trips of -20,000.
We will use these coordinated charts to identify flows that are consistently radically over and under predicted.
Map Tips: Hover mouse over any points to reveal tool tip that contains predicted value, residuals (predicted - actual) and origin / destination bus-stop descriptions.
Show the code
library(plotly)
d <- highlight_key(flowLine2 %>%
filter(dbcRES<= -20000 | dbcRES >= 20000))
unc_rf <- ggplot(data = d,
aes(x = uncTRIPS,
y = uncRES,
text = paste("Origin: ", ORIGIN_DESC, "<br>Destin: ", DESTIN_DESC))) +
geom_point(size = 0.5) +
geom_hline(yintercept = 0, linetype = "dashed", color = "blue")
orc_rf <- ggplot(data = d,
aes(x = orcTRIPS,
y = orcRES,
text = paste("Origin: ", ORIGIN_DESC, "<br>Destin: ", DESTIN_DESC))) +
geom_point(size = 0.5) +
geom_hline(yintercept = 0, linetype = "dashed", color = "blue")
dec_rf <- ggplot(data = d,
aes(x = decTRIPS,
y = decRES,
text = paste("Origin: ", ORIGIN_DESC, "<br>Destin: ", DESTIN_DESC))) +
geom_point(size = 0.5) +
geom_hline(yintercept = 0, linetype = "dashed", color = "blue")
dbc_rf <- ggplot(data = d,
aes(x = dbcTRIPS,
y = dbcRES,
text = paste("Origin: ", ORIGIN_DESC, "<br>Destin: ", DESTIN_DESC))) +
geom_point(size = 0.5) +
geom_hline(yintercept = 0, linetype = "dashed", color = "blue")
subplot(ggplotly(unc_rf),
ggplotly(orc_rf),
ggplotly(dec_rf),
ggplotly(dbc_rf),
nrows = 2,
titleY = TRUE,
titleX = TRUE,
margin = 0.1)Flows that are consistently under-predicted (in big magnitude) in all four models:
Woodlands checkpoint to Woodlands Bus interchange
Woodlands checkpoint to Kranji MRT station
*It appears that trips related to bus stops near the Woodlands Checkpoint tend to be poorly predicted.
Flows that are consistently over-predicted (in big magnitude) in DEC and DBC models:
Woodlands Train to Woodlands Checkpoint
Other interesting Observations:
Flow from Boon Lay MRT to Pioneer MRT station is badly over-predicted in our best model but predicted rather well in all the other 3 models.
Flows from residential Woodlands/ Punggol to Woodlands Bus interchange. Punggol station are also badly over-predicted in our best model but predicted rather well in all the other 3 models.
Visualising the predicted errors flows
Only flows with under-predicted values of more than 30,000 and over-predicted values of above 10,000 are visualised on the maps.
Shades of Blue lines represents under-predicted flows while shades of red lines represents over-predicted flows.
Map Tips: Clicking on a flow line will reveal tooltip containing predicted trips, residuals, origin/destination bus stop descriptions and the distance of the route.
Note: Static trellis plots are available after all the interactive maps below.
Unconstrained Model
Show the code
tmap_mode('view')
tmap_options(check.and.fix = TRUE)
filtered_flowLine <- flowLine2 %>%
filter(uncRES >=10000 | uncRES <= -30000)
bs_count_filtered <- bs_count %>%
filter(grid_id %in% c(filtered_flowLine$ORIGIN_GRID_ID, filtered_flowLine$DESTIN_GRID_ID))
unc <- tm_shape(mpsz) +
tm_polygons(alpha=0.3,
col='black') +
tm_shape(bs_count_filtered) +
tm_polygons(alpha=0.3) +
filtered_flowLine %>%
tm_shape() +
tm_lines(col = 'uncRES',
lwd = 5,
style = 'fixed',
breaks = c(-68000,-40000,-20000,0,20000,40000, 60000, 76000),
#scale= c(0.3, 3, 9, 15, 21, 30),
palette = c("darkblue", "blue", "lightblue", "pink", "red", "darkred"),
#palette = 'RdYlBu',
n = 6,
alpha= 0.9,
popup.vars=c("# Actual Trips:"="TRIPS",
"# Predicted Trips:" = "uncTRIPS",
"Error:" = "uncRES",
"Orig Desc:"="ORIGIN_DESC",
"Destin Desc:" = "DESTIN_DESC",
"Distance:" = 'dist')) +
#col='blue') +
tm_view(set.zoom.limits = c(11,17)) +
tm_layout(main.title = 'Residuals of O-D Flow for Unconstrained SIM' ,
main.title.size = 1.0,
main.title.fontface = 'bold')
uncOrigin-Constrained Model
Show the code
tmap_mode('view')
tmap_options(check.and.fix = TRUE)
filtered_flowLine <- flowLine2 %>%
filter(orcRES >=10000 | orcRES <= -30000)
bs_count_filtered <- bs_count %>%
filter(grid_id %in% c(filtered_flowLine$ORIGIN_GRID_ID, filtered_flowLine$DESTIN_GRID_ID))
orc<- tm_shape(mpsz) +
tm_polygons(alpha=0.3,
col='black') +
tm_shape(bs_count_filtered) +
tm_polygons(alpha=0.3) +
filtered_flowLine %>%
tm_shape() +
tm_lines(col = 'orcRES',
lwd = 5,
style = 'fixed',
breaks = c(-68000,-40000,-20000,0,20000,40000, 60000, 76000),
#scale= c(0.3, 3, 9, 15, 21, 30),
palette = c("darkblue", "blue", "lightblue", "pink", "red", "darkred"),
#palette = 'RdYlBu',
n = 6,
alpha= 0.9,
popup.vars=c("# Actual Trips:"="TRIPS",
"# Predicted Trips:" = "orcTRIPS",
"Error:" = "orcRES",
"Orig Desc:"="ORIGIN_DESC",
"Destin Desc:" = "DESTIN_DESC",
"Distance:" = 'dist')) +
tm_view(set.zoom.limits = c(11,17)) +
tm_layout(main.title = 'Residuals of O-D Flow for Origin Constrained SIM',
main.title.size = 1.0,
main.title.fontface = 'bold')
orcDestination-Constrained Model
Show the code
tmap_mode('view')
tmap_options(check.and.fix = TRUE)
filtered_flowLine <- flowLine2 %>%
filter(decRES >=10000 | decRES <= -30000)
bs_count_filtered <- bs_count %>%
filter(grid_id %in% c(filtered_flowLine$ORIGIN_GRID_ID, filtered_flowLine$DESTIN_GRID_ID))
dec <- tm_shape(mpsz) +
tm_polygons(alpha=0.3,
col='black') +
tm_shape(bs_count_filtered) +
tm_polygons(alpha=0.3,) +
filtered_flowLine %>%
tm_shape() +
tm_lines(col = 'decRES',
lwd = 5,
style = 'fixed',
breaks = c(-68000,-40000,-20000,0,20000,40000, 60000, 76000),
#scale= c(0.3, 3, 9, 15, 21, 30),
palette = c("darkblue", "blue", "lightblue", "pink", "red", "darkred"),
#palette = 'RdYlBu',
n = 6,
alpha= 0.9,
popup.vars=c("# Actual Trips:"="TRIPS",
"# Predicted Trips:" = "decTRIPS",
"Error:" = "decRES",
"Orig Desc:"="ORIGIN_DESC",
"Destin Desc:" = "DESTIN_DESC",
"Distance:" = 'dist')) +
tm_view(set.zoom.limits = c(11,17)) +
tm_layout(main.title = 'Residuals of O-D Flow for Destination Constrained SIM' ,
main.title.size = 1.0,
main.title.fontface = 'bold')
decDoubly-Constrained Model
Show the code
tmap_mode('view')
tmap_options(check.and.fix = TRUE)
filtered_flowLine <- flowLine2 %>%
filter(dbcRES >=10000 | dbcRES <= -30000)
bs_count_filtered <- bs_count %>%
filter(grid_id %in% c(filtered_flowLine$ORIGIN_GRID_ID, filtered_flowLine$DESTIN_GRID_ID))
dbc<- tm_shape(mpsz) +
tm_polygons(alpha=0.3,
col='black') +
tm_shape(bs_count_filtered) +
tm_polygons(alpha=0.3) +
filtered_flowLine %>%
tm_shape() +
tm_lines(col = 'dbcRES',
lwd = 5,
style = 'fixed',
breaks = c(-68000,-40000,-20000,0,20000,40000, 60000, 76000),
#scale= c(0.3, 3, 9, 15, 21, 30),
palette = c("darkblue", "blue", "lightblue", "pink", "red", "darkred"),
#palette = 'RdYlBu',
n = 6,
alpha= 0.9,
popup.vars=c("# Actual Trips:"="TRIPS",
"# Predicted Trips:" = "dbcTRIPS",
"Error:" = "dbcRES",
"Orig Desc:"="ORIGIN_DESC",
"Destin Desc:" = "DESTIN_DESC",
"Distance:" = 'dist')) +
tm_view(set.zoom.limits = c(11,17)) +
tm_layout(main.title = 'Residuals of O-D Flow for Doubly Constrained SIM',
main.title.size = 1.0,
main.title.fontface = 'bold')
dbcWe will plot the residual maps side by side for easy comparison.
Discussion:
At one glance, the unconstrained model tend to under-predict the number of trips than over-predict. The doubly constrained model tend to over-predict the number of trips than to under-predict.
Across all the four models, common regions with high errors in predictions were Woodlands Check Point area, Yishun/Khatib interchange area, Chua Chu Kang interchange area and Boon Lay interchange area. This is because I have used the absolute residual count and these regions have the higher flows in our study area.
Removing the Outliers
In our best performing model (Doubly-Constrained), the flow trips that had the highest error in prediction were associated with areas near the Woodlands Checkpoint.
What if we remove the observations that are close to the Woodlands Checkpoint? Will our model improve?
Two observations to remove:
- Origin_grid_id: 1004 to destin_grid_id: 1108
- Origin_grid_id: 983 to destin_grid_id: 939
Write dbcSM_remove to local
Read dbcSIM_remove back to R
As compared to the original model, removing the outliers improved the model R-squared value from 0.58 to 0.60.
The coefficient of the distance variable is -1.58.
Call:
glm(formula = TRIPS ~ ORIGIN_GRID_ID + DESTIN_GRID_ID + log(dist),
family = poisson(link = "log"), data = flow_data1 %>% filter(!(ORIGIN_GRID_ID ==
1004 & DESTIN_GRID_ID == 1108) & !(ORIGIN_GRID_ID ==
983 & DESTIN_GRID_ID == 939)), na.action = na.exclude)
Deviance Residuals:
Min 1Q Median 3Q Max
-180.77 -9.00 -3.11 2.54 374.93
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 14.4251658 0.1405156 102.659 < 2e-16 ***
ORIGIN_GRID_ID44 1.6986988 0.2004098 8.476 < 2e-16 ***
ORIGIN_GRID_ID46 -0.1442293 0.1618090 -0.891 0.372739
ORIGIN_GRID_ID66 1.4025089 0.1872577 7.490 6.90e-14 ***
ORIGIN_GRID_ID67 1.7880765 0.1317442 13.572 < 2e-16 ***
ORIGIN_GRID_ID68 -0.6411534 0.1732963 -3.700 0.000216 ***
ORIGIN_GRID_ID86 -0.4713554 0.1543779 -3.053 0.002264 **
ORIGIN_GRID_ID87 3.3306401 0.1505678 22.121 < 2e-16 ***
ORIGIN_GRID_ID88 2.3756452 0.1304684 18.209 < 2e-16 ***
ORIGIN_GRID_ID89 0.2047265 0.1389216 1.474 0.140567
ORIGIN_GRID_ID90 0.9039738 0.1837005 4.921 8.61e-07 ***
ORIGIN_GRID_ID109 0.3378554 0.1681025 2.010 0.044451 *
ORIGIN_GRID_ID110 0.5216496 0.1528211 3.413 0.000641 ***
ORIGIN_GRID_ID111 3.9103705 0.1300151 30.076 < 2e-16 ***
ORIGIN_GRID_ID112 0.1021999 0.1479706 0.691 0.489769
ORIGIN_GRID_ID128 3.0503626 0.1328034 22.969 < 2e-16 ***
ORIGIN_GRID_ID129 0.3414217 0.2293965 1.488 0.136659
ORIGIN_GRID_ID130 1.2647621 0.1413068 8.950 < 2e-16 ***
ORIGIN_GRID_ID131 1.8834748 0.1337107 14.086 < 2e-16 ***
ORIGIN_GRID_ID132 0.1698830 0.1412520 1.203 0.229094
ORIGIN_GRID_ID133 1.0756447 0.1360546 7.906 2.66e-15 ***
ORIGIN_GRID_ID134 4.1132924 0.1328080 30.972 < 2e-16 ***
ORIGIN_GRID_ID150 4.1673181 0.1311314 31.780 < 2e-16 ***
ORIGIN_GRID_ID151 0.4327551 0.1535109 2.819 0.004817 **
ORIGIN_GRID_ID152 0.2182293 0.1561763 1.397 0.162315
ORIGIN_GRID_ID153 1.4492868 0.1371591 10.566 < 2e-16 ***
ORIGIN_GRID_ID154 4.1265936 0.1295060 31.864 < 2e-16 ***
ORIGIN_GRID_ID155 0.9698705 0.1351536 7.176 7.17e-13 ***
ORIGIN_GRID_ID156 1.6871586 0.1406692 11.994 < 2e-16 ***
ORIGIN_GRID_ID172 2.2997692 0.1458878 15.764 < 2e-16 ***
ORIGIN_GRID_ID174 1.1000246 0.1381853 7.961 1.71e-15 ***
ORIGIN_GRID_ID175 3.8056106 0.1297994 29.319 < 2e-16 ***
ORIGIN_GRID_ID176 4.8213700 0.1293819 37.265 < 2e-16 ***
ORIGIN_GRID_ID195 -0.0904868 0.1564824 -0.578 0.563091
ORIGIN_GRID_ID196 0.8990375 0.1363229 6.595 4.26e-11 ***
ORIGIN_GRID_ID197 0.0711387 0.1861029 0.382 0.702273
ORIGIN_GRID_ID215 1.4430473 0.1628811 8.860 < 2e-16 ***
ORIGIN_GRID_ID216 5.2356643 0.1295087 40.427 < 2e-16 ***
ORIGIN_GRID_ID217 2.3633744 0.1312675 18.004 < 2e-16 ***
ORIGIN_GRID_ID237 0.4261246 0.3281506 1.299 0.194094
ORIGIN_GRID_ID238 0.8324418 0.1501981 5.542 2.99e-08 ***
ORIGIN_GRID_ID239 1.0969058 0.1939366 5.656 1.55e-08 ***
ORIGIN_GRID_ID257 0.2012811 0.1438792 1.399 0.161825
ORIGIN_GRID_ID258 2.2450326 0.1326353 16.926 < 2e-16 ***
ORIGIN_GRID_ID259 1.4758204 0.1358361 10.865 < 2e-16 ***
ORIGIN_GRID_ID278 1.6210097 0.1350840 12.000 < 2e-16 ***
ORIGIN_GRID_ID279 0.4166645 0.1383879 3.011 0.002605 **
ORIGIN_GRID_ID280 0.9405313 0.1389346 6.770 1.29e-11 ***
ORIGIN_GRID_ID298 -3.1159852 0.3996727 -7.796 6.37e-15 ***
ORIGIN_GRID_ID299 0.1385991 0.1426811 0.971 0.331354
ORIGIN_GRID_ID300 4.1719501 0.1297056 32.165 < 2e-16 ***
ORIGIN_GRID_ID320 -0.2670960 0.1396126 -1.913 0.055732 .
ORIGIN_GRID_ID321 0.8181702 0.1524829 5.366 8.07e-08 ***
ORIGIN_GRID_ID322 2.5725361 0.1357627 18.949 < 2e-16 ***
ORIGIN_GRID_ID340 1.9799854 0.1332403 14.860 < 2e-16 ***
ORIGIN_GRID_ID341 -0.1193750 0.1389837 -0.859 0.390388
ORIGIN_GRID_ID342 1.9964910 0.1363750 14.640 < 2e-16 ***
ORIGIN_GRID_ID363 1.5833417 0.1356031 11.676 < 2e-16 ***
ORIGIN_GRID_ID364 2.1491387 0.1323579 16.237 < 2e-16 ***
ORIGIN_GRID_ID383 1.0429545 0.1338248 7.793 6.52e-15 ***
ORIGIN_GRID_ID384 0.5067183 0.1397336 3.626 0.000287 ***
ORIGIN_GRID_ID385 0.8800834 0.1471725 5.980 2.23e-09 ***
ORIGIN_GRID_ID404 2.1417473 0.1331653 16.083 < 2e-16 ***
ORIGIN_GRID_ID405 0.5403354 0.1412046 3.827 0.000130 ***
ORIGIN_GRID_ID406 5.9802579 0.1294161 46.210 < 2e-16 ***
ORIGIN_GRID_ID407 1.9528361 0.1386937 14.080 < 2e-16 ***
ORIGIN_GRID_ID408 2.6941937 0.1319460 20.419 < 2e-16 ***
ORIGIN_GRID_ID425 -0.6418084 0.1660306 -3.866 0.000111 ***
ORIGIN_GRID_ID426 1.4832282 0.1331422 11.140 < 2e-16 ***
ORIGIN_GRID_ID427 0.6511287 0.1382550 4.710 2.48e-06 ***
ORIGIN_GRID_ID428 0.1174903 0.1799533 0.653 0.513825
ORIGIN_GRID_ID429 2.3263951 0.1312754 17.721 < 2e-16 ***
ORIGIN_GRID_ID446 0.9424908 0.1480959 6.364 1.96e-10 ***
ORIGIN_GRID_ID447 0.9046754 0.1358575 6.659 2.76e-11 ***
ORIGIN_GRID_ID448 1.9528465 0.1324610 14.743 < 2e-16 ***
ORIGIN_GRID_ID449 5.1671155 0.1295949 39.871 < 2e-16 ***
ORIGIN_GRID_ID450 2.1321843 0.1311121 16.262 < 2e-16 ***
ORIGIN_GRID_ID468 1.8025298 0.1335836 13.494 < 2e-16 ***
ORIGIN_GRID_ID469 3.1266737 0.1303617 23.985 < 2e-16 ***
ORIGIN_GRID_ID470 5.2174591 0.1295292 40.280 < 2e-16 ***
ORIGIN_GRID_ID471 2.9984237 0.1306755 22.946 < 2e-16 ***
ORIGIN_GRID_ID488 0.6424425 0.1425042 4.508 6.54e-06 ***
ORIGIN_GRID_ID489 -1.0720629 0.2130419 -5.032 4.85e-07 ***
ORIGIN_GRID_ID490 3.6182230 0.1300351 27.825 < 2e-16 ***
ORIGIN_GRID_ID491 4.1247608 0.1296784 31.808 < 2e-16 ***
ORIGIN_GRID_ID493 -1.6384609 0.2537571 -6.457 1.07e-10 ***
ORIGIN_GRID_ID494 0.7344970 0.1520275 4.831 1.36e-06 ***
ORIGIN_GRID_ID509 0.6639227 0.1352639 4.908 9.18e-07 ***
ORIGIN_GRID_ID510 1.4510991 0.1322760 10.970 < 2e-16 ***
ORIGIN_GRID_ID511 3.0278700 0.1299397 23.302 < 2e-16 ***
ORIGIN_GRID_ID512 5.7469058 0.1294691 44.388 < 2e-16 ***
ORIGIN_GRID_ID513 2.1551729 0.1323928 16.279 < 2e-16 ***
ORIGIN_GRID_ID514 1.3971116 0.1409982 9.909 < 2e-16 ***
ORIGIN_GRID_ID515 -0.0013567 0.2585937 -0.005 0.995814
ORIGIN_GRID_ID530 -0.2711223 0.1580632 -1.715 0.086294 .
ORIGIN_GRID_ID531 1.9404692 0.1311408 14.797 < 2e-16 ***
ORIGIN_GRID_ID532 1.3466659 0.1322585 10.182 < 2e-16 ***
ORIGIN_GRID_ID533 5.4161355 0.1294700 41.833 < 2e-16 ***
ORIGIN_GRID_ID534 6.0350381 0.1294831 46.609 < 2e-16 ***
ORIGIN_GRID_ID536 2.7604811 0.1323586 20.856 < 2e-16 ***
ORIGIN_GRID_ID537 0.4061463 0.2322653 1.749 0.080355 .
ORIGIN_GRID_ID538 0.3226096 0.2888628 1.117 0.264069
ORIGIN_GRID_ID539 0.1595660 1.0089937 0.158 0.874344
ORIGIN_GRID_ID551 -0.2266371 0.1415083 -1.602 0.109248
ORIGIN_GRID_ID552 2.2432632 0.1349663 16.621 < 2e-16 ***
ORIGIN_GRID_ID553 1.8081182 0.1307954 13.824 < 2e-16 ***
ORIGIN_GRID_ID554 5.3528032 0.1294776 41.342 < 2e-16 ***
ORIGIN_GRID_ID555 4.6147239 0.1296765 35.586 < 2e-16 ***
ORIGIN_GRID_ID559 1.1565126 0.1680155 6.883 5.85e-12 ***
ORIGIN_GRID_ID560 3.2630902 0.1414515 23.069 < 2e-16 ***
ORIGIN_GRID_ID561 -1.3475187 1.0097278 -1.335 0.182028
ORIGIN_GRID_ID572 -2.5412843 0.5919805 -4.293 1.76e-05 ***
ORIGIN_GRID_ID573 0.1257970 0.1380119 0.911 0.362035
ORIGIN_GRID_ID574 1.7497630 0.1349795 12.963 < 2e-16 ***
ORIGIN_GRID_ID575 6.3744081 0.1294479 49.243 < 2e-16 ***
ORIGIN_GRID_ID576 4.9700282 0.1295353 38.368 < 2e-16 ***
ORIGIN_GRID_ID578 0.3668415 0.1662811 2.206 0.027373 *
ORIGIN_GRID_ID582 0.6232946 0.1702474 3.661 0.000251 ***
ORIGIN_GRID_ID583 1.5639487 0.5918994 2.642 0.008236 **
ORIGIN_GRID_ID584 3.9563636 0.1421212 27.838 < 2e-16 ***
ORIGIN_GRID_ID593 1.3207275 0.1396698 9.456 < 2e-16 ***
ORIGIN_GRID_ID594 1.3966248 0.1321928 10.565 < 2e-16 ***
ORIGIN_GRID_ID595 1.6601522 0.1309842 12.674 < 2e-16 ***
ORIGIN_GRID_ID596 4.7108655 0.1295076 36.375 < 2e-16 ***
ORIGIN_GRID_ID597 1.9941325 0.1432509 13.921 < 2e-16 ***
ORIGIN_GRID_ID603 1.1699427 0.1754515 6.668 2.59e-11 ***
ORIGIN_GRID_ID604 1.6111956 0.2319507 6.946 3.75e-12 ***
ORIGIN_GRID_ID615 -0.0681062 0.1391052 -0.490 0.624415
ORIGIN_GRID_ID616 1.1194802 0.1336039 8.379 < 2e-16 ***
ORIGIN_GRID_ID617 2.0178856 0.1308794 15.418 < 2e-16 ***
ORIGIN_GRID_ID618 5.3976548 0.1294908 41.684 < 2e-16 ***
ORIGIN_GRID_ID620 2.7526957 0.1334254 20.631 < 2e-16 ***
ORIGIN_GRID_ID637 0.8296222 0.1372290 6.046 1.49e-09 ***
ORIGIN_GRID_ID638 4.8129105 0.1295069 37.163 < 2e-16 ***
ORIGIN_GRID_ID657 2.6557255 0.1306377 20.329 < 2e-16 ***
ORIGIN_GRID_ID658 4.1579815 0.1296088 32.081 < 2e-16 ***
ORIGIN_GRID_ID659 4.3727093 0.1295592 33.751 < 2e-16 ***
ORIGIN_GRID_ID660 5.4496107 0.1294834 42.087 < 2e-16 ***
ORIGIN_GRID_ID662 5.5779508 0.1296664 43.018 < 2e-16 ***
ORIGIN_GRID_ID677 2.5501490 0.1316660 19.368 < 2e-16 ***
ORIGIN_GRID_ID678 0.3522716 0.1388049 2.538 0.011152 *
ORIGIN_GRID_ID679 5.3757896 0.1294914 41.515 < 2e-16 ***
ORIGIN_GRID_ID680 5.6350416 0.1294903 43.517 < 2e-16 ***
ORIGIN_GRID_ID681 4.3769019 0.1297418 33.735 < 2e-16 ***
ORIGIN_GRID_ID699 2.0653818 0.1316442 15.689 < 2e-16 ***
ORIGIN_GRID_ID700 4.3631497 0.1295945 33.668 < 2e-16 ***
ORIGIN_GRID_ID701 4.2470202 0.1295974 32.771 < 2e-16 ***
ORIGIN_GRID_ID702 5.2963693 0.1294892 40.902 < 2e-16 ***
ORIGIN_GRID_ID704 2.4068882 0.1339689 17.966 < 2e-16 ***
ORIGIN_GRID_ID722 2.0194257 0.1310842 15.406 < 2e-16 ***
ORIGIN_GRID_ID725 1.9676040 0.1360880 14.458 < 2e-16 ***
ORIGIN_GRID_ID741 2.6279618 0.1305727 20.126 < 2e-16 ***
ORIGIN_GRID_ID743 2.8050923 0.1301462 21.553 < 2e-16 ***
ORIGIN_GRID_ID744 4.8341525 0.1295289 37.321 < 2e-16 ***
ORIGIN_GRID_ID761 2.0660476 0.1330286 15.531 < 2e-16 ***
ORIGIN_GRID_ID762 4.1330832 0.1296645 31.875 < 2e-16 ***
ORIGIN_GRID_ID763 1.2868812 0.1329841 9.677 < 2e-16 ***
ORIGIN_GRID_ID764 5.3531937 0.1294888 41.341 < 2e-16 ***
ORIGIN_GRID_ID765 4.6323360 0.1297350 35.706 < 2e-16 ***
ORIGIN_GRID_ID767 6.4740275 0.1295035 49.991 < 2e-16 ***
ORIGIN_GRID_ID772 1.2307451 0.1532737 8.030 9.77e-16 ***
ORIGIN_GRID_ID784 1.2152606 0.1325924 9.165 < 2e-16 ***
ORIGIN_GRID_ID785 4.5169907 0.1295193 34.875 < 2e-16 ***
ORIGIN_GRID_ID786 4.2259831 0.1295980 32.608 < 2e-16 ***
ORIGIN_GRID_ID787 4.8075423 0.1296689 37.076 < 2e-16 ***
ORIGIN_GRID_ID788 5.6871377 0.1295691 43.893 < 2e-16 ***
ORIGIN_GRID_ID789 4.1289701 0.1299360 31.777 < 2e-16 ***
ORIGIN_GRID_ID803 0.1040210 0.1447637 0.719 0.472414
ORIGIN_GRID_ID804 5.1541795 0.1295150 39.796 < 2e-16 ***
ORIGIN_GRID_ID805 5.1684091 0.1294886 39.914 < 2e-16 ***
ORIGIN_GRID_ID806 4.8467057 0.1295183 37.421 < 2e-16 ***
ORIGIN_GRID_ID807 5.8919616 0.1295210 45.490 < 2e-16 ***
ORIGIN_GRID_ID808 4.1105652 0.1299600 31.629 < 2e-16 ***
ORIGIN_GRID_ID809 5.8597364 0.1294948 45.251 < 2e-16 ***
ORIGIN_GRID_ID810 5.1041569 0.1295952 39.385 < 2e-16 ***
ORIGIN_GRID_ID814 3.1615912 0.1325776 23.847 < 2e-16 ***
ORIGIN_GRID_ID819 5.0778251 0.1310004 38.762 < 2e-16 ***
ORIGIN_GRID_ID824 1.2128965 0.1361808 8.907 < 2e-16 ***
ORIGIN_GRID_ID826 2.7923123 0.1298909 21.497 < 2e-16 ***
ORIGIN_GRID_ID827 4.7931678 0.1295064 37.011 < 2e-16 ***
ORIGIN_GRID_ID828 5.2041232 0.1294989 40.187 < 2e-16 ***
ORIGIN_GRID_ID829 5.2586828 0.1295313 40.598 < 2e-16 ***
ORIGIN_GRID_ID830 5.5479552 0.1295551 42.823 < 2e-16 ***
ORIGIN_GRID_ID831 6.3992759 0.1294790 49.423 < 2e-16 ***
ORIGIN_GRID_ID832 5.4813948 0.1296409 42.281 < 2e-16 ***
ORIGIN_GRID_ID835 3.1282524 0.1329243 23.534 < 2e-16 ***
ORIGIN_GRID_ID844 0.2991872 0.1512352 1.978 0.047896 *
ORIGIN_GRID_ID846 4.2038603 0.1295650 32.446 < 2e-16 ***
ORIGIN_GRID_ID847 3.2122313 0.1298650 24.735 < 2e-16 ***
ORIGIN_GRID_ID848 4.5721929 0.1295400 35.296 < 2e-16 ***
ORIGIN_GRID_ID849 3.8256935 0.1296987 29.497 < 2e-16 ***
ORIGIN_GRID_ID850 4.6766139 0.1295776 36.091 < 2e-16 ***
ORIGIN_GRID_ID851 5.2812200 0.1295168 40.776 < 2e-16 ***
ORIGIN_GRID_ID852 4.8204659 0.1296170 37.190 < 2e-16 ***
ORIGIN_GRID_ID853 6.8096303 0.1295265 52.573 < 2e-16 ***
ORIGIN_GRID_ID854 3.4076881 0.1321773 25.781 < 2e-16 ***
ORIGIN_GRID_ID855 1.9770372 0.1373321 14.396 < 2e-16 ***
ORIGIN_GRID_ID856 3.5440560 0.1309401 27.066 < 2e-16 ***
ORIGIN_GRID_ID866 2.1329959 0.1326311 16.082 < 2e-16 ***
ORIGIN_GRID_ID867 3.0464895 0.1300555 23.425 < 2e-16 ***
ORIGIN_GRID_ID868 2.0888853 0.1312924 15.910 < 2e-16 ***
ORIGIN_GRID_ID869 4.9901894 0.1295909 38.507 < 2e-16 ***
ORIGIN_GRID_ID870 5.7473571 0.1294771 44.389 < 2e-16 ***
ORIGIN_GRID_ID871 5.5538695 0.1295984 42.854 < 2e-16 ***
ORIGIN_GRID_ID872 3.4684285 0.1299884 26.683 < 2e-16 ***
ORIGIN_GRID_ID873 3.6860083 0.1299035 28.375 < 2e-16 ***
ORIGIN_GRID_ID874 4.0432441 0.1297215 31.169 < 2e-16 ***
ORIGIN_GRID_ID875 1.0468831 0.1470988 7.117 1.10e-12 ***
ORIGIN_GRID_ID876 2.3600577 0.1333019 17.705 < 2e-16 ***
ORIGIN_GRID_ID877 1.8428688 0.1364803 13.503 < 2e-16 ***
ORIGIN_GRID_ID887 2.4407408 0.1302368 18.741 < 2e-16 ***
ORIGIN_GRID_ID888 3.9022078 0.1296645 30.095 < 2e-16 ***
ORIGIN_GRID_ID889 0.8208570 0.1340842 6.122 9.24e-10 ***
ORIGIN_GRID_ID890 5.1919487 0.1294982 40.093 < 2e-16 ***
ORIGIN_GRID_ID891 3.9215880 0.1299870 30.169 < 2e-16 ***
ORIGIN_GRID_ID893 5.3390335 0.1295095 41.225 < 2e-16 ***
ORIGIN_GRID_ID894 3.5891672 0.1299016 27.630 < 2e-16 ***
ORIGIN_GRID_ID895 3.0959215 0.1304192 23.738 < 2e-16 ***
ORIGIN_GRID_ID896 1.9338332 0.1331830 14.520 < 2e-16 ***
ORIGIN_GRID_ID897 0.4833247 0.1496375 3.230 0.001238 **
ORIGIN_GRID_ID898 2.6137466 0.1337339 19.544 < 2e-16 ***
ORIGIN_GRID_ID908 3.9006361 0.1300968 29.983 < 2e-16 ***
ORIGIN_GRID_ID909 3.9098447 0.1295880 30.171 < 2e-16 ***
ORIGIN_GRID_ID910 2.0504914 0.1305978 15.701 < 2e-16 ***
ORIGIN_GRID_ID911 3.3409428 0.1297925 25.741 < 2e-16 ***
ORIGIN_GRID_ID912 4.9174620 0.1295175 37.968 < 2e-16 ***
ORIGIN_GRID_ID915 5.2347442 0.1295215 40.416 < 2e-16 ***
ORIGIN_GRID_ID917 4.8541034 0.1296684 37.435 < 2e-16 ***
ORIGIN_GRID_ID918 1.3918892 0.1360563 10.230 < 2e-16 ***
ORIGIN_GRID_ID919 4.5903239 0.1298055 35.363 < 2e-16 ***
ORIGIN_GRID_ID928 2.7474936 0.1303422 21.079 < 2e-16 ***
ORIGIN_GRID_ID929 4.3414508 0.1295290 33.517 < 2e-16 ***
ORIGIN_GRID_ID930 5.1860408 0.1294802 40.053 < 2e-16 ***
ORIGIN_GRID_ID931 2.1489697 0.1307355 16.438 < 2e-16 ***
ORIGIN_GRID_ID932 2.6728727 0.1307589 20.441 < 2e-16 ***
ORIGIN_GRID_ID933 4.7817745 0.1295784 36.903 < 2e-16 ***
ORIGIN_GRID_ID934 2.2432938 0.1310276 17.121 < 2e-16 ***
ORIGIN_GRID_ID935 6.1038681 0.1294782 47.142 < 2e-16 ***
ORIGIN_GRID_ID938 -1.8803204 0.3061097 -6.143 8.12e-10 ***
ORIGIN_GRID_ID939 5.9608124 0.1295217 46.022 < 2e-16 ***
ORIGIN_GRID_ID940 0.1347099 0.1603278 0.840 0.400787
ORIGIN_GRID_ID949 2.6020130 0.1302897 19.971 < 2e-16 ***
ORIGIN_GRID_ID950 4.7595971 0.1295496 36.740 < 2e-16 ***
ORIGIN_GRID_ID951 5.6181849 0.1294714 43.393 < 2e-16 ***
ORIGIN_GRID_ID952 2.3302242 0.1313903 17.735 < 2e-16 ***
ORIGIN_GRID_ID953 3.4985428 0.1298533 26.942 < 2e-16 ***
ORIGIN_GRID_ID954 2.3888285 0.1307463 18.271 < 2e-16 ***
ORIGIN_GRID_ID955 4.6514934 0.1295793 35.897 < 2e-16 ***
ORIGIN_GRID_ID956 3.0577070 0.1300285 23.516 < 2e-16 ***
ORIGIN_GRID_ID957 5.2360151 0.1295854 40.406 < 2e-16 ***
ORIGIN_GRID_ID959 1.2004316 0.1401430 8.566 < 2e-16 ***
ORIGIN_GRID_ID961 1.3723500 0.1343157 10.217 < 2e-16 ***
ORIGIN_GRID_ID962 6.2932861 0.1296601 48.537 < 2e-16 ***
ORIGIN_GRID_ID970 3.1658454 0.1297318 24.403 < 2e-16 ***
ORIGIN_GRID_ID971 4.4975937 0.1295045 34.729 < 2e-16 ***
ORIGIN_GRID_ID972 4.4398815 0.1295337 34.276 < 2e-16 ***
ORIGIN_GRID_ID974 4.0405654 0.1296797 31.158 < 2e-16 ***
ORIGIN_GRID_ID975 3.6991397 0.1297856 28.502 < 2e-16 ***
ORIGIN_GRID_ID976 2.4419048 0.1306195 18.695 < 2e-16 ***
ORIGIN_GRID_ID977 5.6177291 0.1294993 43.380 < 2e-16 ***
ORIGIN_GRID_ID978 5.5207145 0.1296465 42.583 < 2e-16 ***
ORIGIN_GRID_ID982 2.3746527 0.1305508 18.189 < 2e-16 ***
ORIGIN_GRID_ID983 5.9982169 0.1296413 46.268 < 2e-16 ***
ORIGIN_GRID_ID984 7.4839954 0.1296185 57.739 < 2e-16 ***
ORIGIN_GRID_ID991 3.1460784 0.1298188 24.234 < 2e-16 ***
ORIGIN_GRID_ID992 3.5161231 0.1296479 27.121 < 2e-16 ***
ORIGIN_GRID_ID993 3.2012980 0.1296974 24.683 < 2e-16 ***
ORIGIN_GRID_ID994 2.7522790 0.1299916 21.173 < 2e-16 ***
ORIGIN_GRID_ID995 4.2373831 0.1295792 32.701 < 2e-16 ***
ORIGIN_GRID_ID996 3.9327477 0.1297030 30.321 < 2e-16 ***
ORIGIN_GRID_ID997 2.6883270 0.1328873 20.230 < 2e-16 ***
ORIGIN_GRID_ID998 5.7266967 0.1295043 44.220 < 2e-16 ***
ORIGIN_GRID_ID999 5.7029596 0.1295823 44.010 < 2e-16 ***
ORIGIN_GRID_ID1001 2.6003084 0.1320336 19.694 < 2e-16 ***
ORIGIN_GRID_ID1003 5.2863424 0.1295285 40.812 < 2e-16 ***
ORIGIN_GRID_ID1004 5.3405482 0.1295329 41.229 < 2e-16 ***
ORIGIN_GRID_ID1011 1.3647604 0.1339480 10.189 < 2e-16 ***
ORIGIN_GRID_ID1012 0.9456500 0.1360398 6.951 3.62e-12 ***
ORIGIN_GRID_ID1013 1.8362300 0.1308337 14.035 < 2e-16 ***
ORIGIN_GRID_ID1014 2.7362343 0.1299917 21.049 < 2e-16 ***
ORIGIN_GRID_ID1015 2.0345836 0.1307994 15.555 < 2e-16 ***
ORIGIN_GRID_ID1016 3.8670135 0.1296923 29.817 < 2e-16 ***
ORIGIN_GRID_ID1018 4.6086701 0.1298495 35.492 < 2e-16 ***
ORIGIN_GRID_ID1019 6.1358069 0.1295426 47.365 < 2e-16 ***
ORIGIN_GRID_ID1023 4.1977330 0.1298157 32.336 < 2e-16 ***
ORIGIN_GRID_ID1024 5.2673824 0.1295392 40.662 < 2e-16 ***
ORIGIN_GRID_ID1025 0.4331456 0.1461907 2.963 0.003048 **
ORIGIN_GRID_ID1033 2.4801849 0.1301128 19.062 < 2e-16 ***
ORIGIN_GRID_ID1034 3.5007183 0.1296874 26.994 < 2e-16 ***
ORIGIN_GRID_ID1035 4.2760392 0.1295687 33.002 < 2e-16 ***
ORIGIN_GRID_ID1036 2.0668655 0.1307309 15.810 < 2e-16 ***
ORIGIN_GRID_ID1037 3.4801973 0.1296792 26.837 < 2e-16 ***
ORIGIN_GRID_ID1043 2.5347617 0.1322070 19.173 < 2e-16 ***
ORIGIN_GRID_ID1045 4.9347318 0.1295347 38.096 < 2e-16 ***
ORIGIN_GRID_ID1046 4.8966432 0.1295649 37.793 < 2e-16 ***
ORIGIN_GRID_ID1053 4.0790315 0.1295969 31.475 < 2e-16 ***
ORIGIN_GRID_ID1054 2.9560343 0.1297861 22.776 < 2e-16 ***
ORIGIN_GRID_ID1055 4.1366811 0.1295624 31.928 < 2e-16 ***
ORIGIN_GRID_ID1056 3.1384722 0.1298367 24.172 < 2e-16 ***
ORIGIN_GRID_ID1064 0.2529711 0.2889114 0.876 0.381247
ORIGIN_GRID_ID1066 4.7040533 0.1295634 36.307 < 2e-16 ***
ORIGIN_GRID_ID1067 -0.9908470 0.2417401 -4.099 4.15e-05 ***
ORIGIN_GRID_ID1074 3.3647158 0.1297246 25.937 < 2e-16 ***
ORIGIN_GRID_ID1075 2.5519276 0.1300191 19.627 < 2e-16 ***
ORIGIN_GRID_ID1076 2.8410875 0.1297909 21.890 < 2e-16 ***
ORIGIN_GRID_ID1077 3.0008935 0.1299373 23.095 < 2e-16 ***
ORIGIN_GRID_ID1079 4.4005249 0.1295718 33.962 < 2e-16 ***
ORIGIN_GRID_ID1085 -1.4752692 0.2215626 -6.658 2.77e-11 ***
ORIGIN_GRID_ID1087 4.7462577 0.1295950 36.624 < 2e-16 ***
ORIGIN_GRID_ID1088 3.0009003 0.1300631 23.073 < 2e-16 ***
ORIGIN_GRID_ID1094 1.3897889 0.1386609 10.023 < 2e-16 ***
ORIGIN_GRID_ID1095 0.7936824 0.1368159 5.801 6.59e-09 ***
ORIGIN_GRID_ID1096 2.8291150 0.1314529 21.522 < 2e-16 ***
ORIGIN_GRID_ID1097 4.7977885 0.1295045 37.047 < 2e-16 ***
ORIGIN_GRID_ID1098 2.3958521 0.1309856 18.291 < 2e-16 ***
ORIGIN_GRID_ID1099 3.8152663 0.1296520 29.427 < 2e-16 ***
ORIGIN_GRID_ID1105 1.3177087 0.1520039 8.669 < 2e-16 ***
ORIGIN_GRID_ID1106 -0.2033498 0.1726077 -1.178 0.238755
ORIGIN_GRID_ID1107 2.3780426 0.1331017 17.866 < 2e-16 ***
ORIGIN_GRID_ID1108 6.5489351 0.1294783 50.579 < 2e-16 ***
ORIGIN_GRID_ID1109 1.7087473 0.1324328 12.903 < 2e-16 ***
ORIGIN_GRID_ID1116 3.1806567 0.1297892 24.506 < 2e-16 ***
ORIGIN_GRID_ID1117 1.5107910 0.1314793 11.491 < 2e-16 ***
ORIGIN_GRID_ID1118 2.0017458 0.1310998 15.269 < 2e-16 ***
ORIGIN_GRID_ID1119 2.9868469 0.1299429 22.986 < 2e-16 ***
ORIGIN_GRID_ID1120 2.9456861 0.1302808 22.610 < 2e-16 ***
ORIGIN_GRID_ID1129 5.0754948 0.1295516 39.177 < 2e-16 ***
ORIGIN_GRID_ID1130 5.0687874 0.1295194 39.135 < 2e-16 ***
ORIGIN_GRID_ID1131 2.9766761 0.1305694 22.798 < 2e-16 ***
ORIGIN_GRID_ID1136 2.2212553 0.1303989 17.034 < 2e-16 ***
ORIGIN_GRID_ID1138 1.0220132 0.1357068 7.531 5.03e-14 ***
ORIGIN_GRID_ID1139 3.9730594 0.1295671 30.664 < 2e-16 ***
ORIGIN_GRID_ID1141 3.9391443 0.1296222 30.389 < 2e-16 ***
ORIGIN_GRID_ID1148 1.5159962 0.1388321 10.920 < 2e-16 ***
ORIGIN_GRID_ID1149 2.8193183 0.1310135 21.519 < 2e-16 ***
ORIGIN_GRID_ID1150 5.3050466 0.1295094 40.963 < 2e-16 ***
ORIGIN_GRID_ID1151 4.1390526 0.1296330 31.929 < 2e-16 ***
ORIGIN_GRID_ID1158 2.2664512 0.1300688 17.425 < 2e-16 ***
ORIGIN_GRID_ID1159 3.7553837 0.1295912 28.979 < 2e-16 ***
ORIGIN_GRID_ID1160 4.7975884 0.1295070 37.045 < 2e-16 ***
ORIGIN_GRID_ID1171 5.8734835 0.1295205 45.348 < 2e-16 ***
ORIGIN_GRID_ID1172 5.6664149 0.1295176 43.750 < 2e-16 ***
ORIGIN_GRID_ID1173 2.8932903 0.1301767 22.226 < 2e-16 ***
ORIGIN_GRID_ID1174 -1.3503970 0.2888987 -4.674 2.95e-06 ***
ORIGIN_GRID_ID1178 2.5060113 0.1299982 19.277 < 2e-16 ***
ORIGIN_GRID_ID1179 3.1787054 0.1296857 24.511 < 2e-16 ***
ORIGIN_GRID_ID1180 4.2790617 0.1295314 33.035 < 2e-16 ***
ORIGIN_GRID_ID1181 3.5643239 0.1296487 27.492 < 2e-16 ***
ORIGIN_GRID_ID1183 2.6594906 0.1302535 20.418 < 2e-16 ***
ORIGIN_GRID_ID1190 1.6055290 0.1390711 11.545 < 2e-16 ***
ORIGIN_GRID_ID1192 4.5473435 0.1296296 35.080 < 2e-16 ***
ORIGIN_GRID_ID1193 4.5019376 0.1295768 34.743 < 2e-16 ***
ORIGIN_GRID_ID1194 2.6889240 0.1304028 20.620 < 2e-16 ***
ORIGIN_GRID_ID1200 3.3472734 0.1296558 25.817 < 2e-16 ***
ORIGIN_GRID_ID1201 3.1248740 0.1296955 24.094 < 2e-16 ***
ORIGIN_GRID_ID1203 4.0322141 0.1296058 31.111 < 2e-16 ***
ORIGIN_GRID_ID1204 3.8764315 0.1296287 29.904 < 2e-16 ***
ORIGIN_GRID_ID1211 0.3945267 0.2538798 1.554 0.120187
ORIGIN_GRID_ID1214 5.3296933 0.1295270 41.147 < 2e-16 ***
ORIGIN_GRID_ID1215 1.7370602 0.1368589 12.692 < 2e-16 ***
ORIGIN_GRID_ID1216 0.7854478 0.1365190 5.753 8.75e-09 ***
ORIGIN_GRID_ID1220 4.2997603 0.1295300 33.195 < 2e-16 ***
ORIGIN_GRID_ID1221 3.9931191 0.1295431 30.825 < 2e-16 ***
ORIGIN_GRID_ID1222 3.6559472 0.1298962 28.145 < 2e-16 ***
ORIGIN_GRID_ID1223 1.9429674 0.1308637 14.847 < 2e-16 ***
ORIGIN_GRID_ID1224 2.8131307 0.1299910 21.641 < 2e-16 ***
ORIGIN_GRID_ID1231 -1.1001334 0.2382821 -4.617 3.89e-06 ***
ORIGIN_GRID_ID1232 1.5279050 0.1571607 9.722 < 2e-16 ***
ORIGIN_GRID_ID1235 2.8291608 0.1302548 21.720 < 2e-16 ***
ORIGIN_GRID_ID1236 2.5793950 0.1303669 19.786 < 2e-16 ***
ORIGIN_GRID_ID1241 2.5226607 0.1299718 19.409 < 2e-16 ***
ORIGIN_GRID_ID1242 3.1963379 0.1296642 24.651 < 2e-16 ***
ORIGIN_GRID_ID1243 3.8058850 0.1295625 29.375 < 2e-16 ***
ORIGIN_GRID_ID1246 2.9942682 0.1298666 23.056 < 2e-16 ***
ORIGIN_GRID_ID1256 4.2819698 0.1296827 33.019 < 2e-16 ***
ORIGIN_GRID_ID1257 5.1743573 0.1295790 39.932 < 2e-16 ***
ORIGIN_GRID_ID1258 3.0843780 0.1303267 23.667 < 2e-16 ***
ORIGIN_GRID_ID1262 2.9674123 0.1297705 22.867 < 2e-16 ***
ORIGIN_GRID_ID1263 3.4035814 0.1295932 26.264 < 2e-16 ***
ORIGIN_GRID_ID1264 2.3875098 0.1302330 18.333 < 2e-16 ***
ORIGIN_GRID_ID1265 2.0633303 0.1307124 15.785 < 2e-16 ***
ORIGIN_GRID_ID1266 3.6995744 0.1297067 28.523 < 2e-16 ***
ORIGIN_GRID_ID1267 1.5877485 0.1336306 11.882 < 2e-16 ***
ORIGIN_GRID_ID1272 -0.7986926 0.1962372 -4.070 4.70e-05 ***
ORIGIN_GRID_ID1273 3.5489402 0.1301352 27.271 < 2e-16 ***
ORIGIN_GRID_ID1277 5.2191450 0.1295289 40.293 < 2e-16 ***
ORIGIN_GRID_ID1278 2.5850269 0.1303158 19.837 < 2e-16 ***
ORIGIN_GRID_ID1283 4.6757234 0.1295199 36.100 < 2e-16 ***
ORIGIN_GRID_ID1284 3.9464974 0.1295560 30.462 < 2e-16 ***
ORIGIN_GRID_ID1285 4.5776562 0.1295036 35.348 < 2e-16 ***
ORIGIN_GRID_ID1286 2.7632683 0.1300119 21.254 < 2e-16 ***
ORIGIN_GRID_ID1289 1.1161063 0.1403926 7.950 1.87e-15 ***
ORIGIN_GRID_ID1293 0.2650562 0.1533829 1.728 0.083976 .
ORIGIN_GRID_ID1294 5.0443666 0.1296145 38.918 < 2e-16 ***
ORIGIN_GRID_ID1295 2.4858665 0.1314296 18.914 < 2e-16 ***
ORIGIN_GRID_ID1298 4.2997145 0.1296525 33.163 < 2e-16 ***
ORIGIN_GRID_ID1299 4.6495288 0.1296161 35.872 < 2e-16 ***
ORIGIN_GRID_ID1304 4.5822559 0.1295185 35.379 < 2e-16 ***
ORIGIN_GRID_ID1305 3.9403926 0.1295297 30.421 < 2e-16 ***
ORIGIN_GRID_ID1307 0.1595614 0.1400368 1.139 0.254526
ORIGIN_GRID_ID1308 3.7606637 0.1296321 29.010 < 2e-16 ***
ORIGIN_GRID_ID1310 -1.0827443 0.2689184 -4.026 5.67e-05 ***
ORIGIN_GRID_ID1316 1.5878952 0.1344850 11.807 < 2e-16 ***
ORIGIN_GRID_ID1317 3.2639713 0.1300179 25.104 < 2e-16 ***
ORIGIN_GRID_ID1318 2.5602756 0.1305420 19.613 < 2e-16 ***
ORIGIN_GRID_ID1319 5.5219006 0.1295204 42.633 < 2e-16 ***
ORIGIN_GRID_ID1320 4.0668524 0.1297837 31.336 < 2e-16 ***
ORIGIN_GRID_ID1325 2.1843522 0.1301657 16.781 < 2e-16 ***
ORIGIN_GRID_ID1326 4.1488650 0.1295251 32.031 < 2e-16 ***
ORIGIN_GRID_ID1327 3.8838976 0.1295496 29.980 < 2e-16 ***
ORIGIN_GRID_ID1328 2.5016267 0.1299283 19.254 < 2e-16 ***
ORIGIN_GRID_ID1329 2.7954768 0.1301131 21.485 < 2e-16 ***
ORIGIN_GRID_ID1330 3.6743144 0.1297640 28.315 < 2e-16 ***
ORIGIN_GRID_ID1331 -1.3211288 0.3576104 -3.694 0.000220 ***
ORIGIN_GRID_ID1333 3.0893113 0.1301351 23.739 < 2e-16 ***
ORIGIN_GRID_ID1334 3.3510441 0.1300405 25.769 < 2e-16 ***
ORIGIN_GRID_ID1335 2.9565470 0.1307090 22.619 < 2e-16 ***
ORIGIN_GRID_ID1336 0.1305294 0.1897176 0.688 0.491441
ORIGIN_GRID_ID1337 0.5318491 0.1417560 3.752 0.000176 ***
ORIGIN_GRID_ID1338 -0.8686145 0.1724803 -5.036 4.75e-07 ***
ORIGIN_GRID_ID1339 5.3557540 0.1295162 41.352 < 2e-16 ***
ORIGIN_GRID_ID1340 3.7793936 0.1297861 29.120 < 2e-16 ***
ORIGIN_GRID_ID1341 0.8988677 0.2584336 3.478 0.000505 ***
ORIGIN_GRID_ID1346 3.7683777 0.1296356 29.069 < 2e-16 ***
ORIGIN_GRID_ID1347 4.7676191 0.1295051 36.814 < 2e-16 ***
ORIGIN_GRID_ID1348 3.1160250 0.1296532 24.034 < 2e-16 ***
ORIGIN_GRID_ID1349 2.9404331 0.1298037 22.653 < 2e-16 ***
ORIGIN_GRID_ID1350 3.2787344 0.1299903 25.223 < 2e-16 ***
ORIGIN_GRID_ID1353 3.0938199 0.1298968 23.818 < 2e-16 ***
ORIGIN_GRID_ID1354 2.8560623 0.1301852 21.938 < 2e-16 ***
ORIGIN_GRID_ID1355 3.6801503 0.1297720 28.359 < 2e-16 ***
ORIGIN_GRID_ID1357 2.7137527 0.1310843 20.702 < 2e-16 ***
ORIGIN_GRID_ID1358 4.1194421 0.1296856 31.765 < 2e-16 ***
ORIGIN_GRID_ID1359 4.4041268 0.1295744 33.989 < 2e-16 ***
ORIGIN_GRID_ID1360 4.5347139 0.1295763 34.996 < 2e-16 ***
ORIGIN_GRID_ID1361 5.6356077 0.1295290 43.508 < 2e-16 ***
ORIGIN_GRID_ID1362 1.7498226 0.1359619 12.870 < 2e-16 ***
ORIGIN_GRID_ID1368 2.6347130 0.1298041 20.298 < 2e-16 ***
ORIGIN_GRID_ID1369 2.3405270 0.1298664 18.023 < 2e-16 ***
ORIGIN_GRID_ID1370 3.5740928 0.1295730 27.584 < 2e-16 ***
ORIGIN_GRID_ID1371 2.9585602 0.1299312 22.770 < 2e-16 ***
ORIGIN_GRID_ID1372 2.2729839 0.1301954 17.458 < 2e-16 ***
ORIGIN_GRID_ID1373 0.6559498 0.1397495 4.694 2.68e-06 ***
ORIGIN_GRID_ID1374 2.5822642 0.1300911 19.850 < 2e-16 ***
ORIGIN_GRID_ID1375 4.1219102 0.1297204 31.775 < 2e-16 ***
ORIGIN_GRID_ID1376 3.4160906 0.1301978 26.238 < 2e-16 ***
ORIGIN_GRID_ID1379 1.7430272 0.1344517 12.964 < 2e-16 ***
ORIGIN_GRID_ID1380 5.7447909 0.1294932 44.364 < 2e-16 ***
ORIGIN_GRID_ID1381 5.3362103 0.1295157 41.201 < 2e-16 ***
ORIGIN_GRID_ID1382 4.8380336 0.1296212 37.324 < 2e-16 ***
ORIGIN_GRID_ID1383 2.4535486 0.1320024 18.587 < 2e-16 ***
ORIGIN_GRID_ID1388 3.1702473 0.1296661 24.449 < 2e-16 ***
ORIGIN_GRID_ID1389 1.9138532 0.1300732 14.714 < 2e-16 ***
ORIGIN_GRID_ID1390 3.0598944 0.1296808 23.596 < 2e-16 ***
ORIGIN_GRID_ID1391 3.1493540 0.1297316 24.276 < 2e-16 ***
ORIGIN_GRID_ID1392 2.6505463 0.1308345 20.259 < 2e-16 ***
ORIGIN_GRID_ID1393 1.8245983 0.1304814 13.984 < 2e-16 ***
ORIGIN_GRID_ID1394 3.2771008 0.1297126 25.264 < 2e-16 ***
ORIGIN_GRID_ID1395 3.3561832 0.1297108 25.874 < 2e-16 ***
ORIGIN_GRID_ID1396 4.4704817 0.1295616 34.505 < 2e-16 ***
ORIGIN_GRID_ID1397 4.5465139 0.1295705 35.089 < 2e-16 ***
ORIGIN_GRID_ID1398 3.4779303 0.1299875 26.756 < 2e-16 ***
ORIGIN_GRID_ID1400 4.6627061 0.1296299 35.969 < 2e-16 ***
ORIGIN_GRID_ID1401 5.7750400 0.1294877 44.599 < 2e-16 ***
ORIGIN_GRID_ID1402 5.0074999 0.1295370 38.657 < 2e-16 ***
ORIGIN_GRID_ID1404 5.1209871 0.1304493 39.257 < 2e-16 ***
ORIGIN_GRID_ID1410 2.6854617 0.1297403 20.699 < 2e-16 ***
ORIGIN_GRID_ID1411 2.7277436 0.1297623 21.021 < 2e-16 ***
ORIGIN_GRID_ID1412 2.9944360 0.1296529 23.096 < 2e-16 ***
ORIGIN_GRID_ID1413 3.8876122 0.1295688 30.004 < 2e-16 ***
ORIGIN_GRID_ID1414 3.2629948 0.1296365 25.170 < 2e-16 ***
ORIGIN_GRID_ID1415 2.8087009 0.1298467 21.631 < 2e-16 ***
ORIGIN_GRID_ID1416 3.4856181 0.1296622 26.882 < 2e-16 ***
ORIGIN_GRID_ID1417 3.6246144 0.1296443 27.958 < 2e-16 ***
ORIGIN_GRID_ID1418 4.4431908 0.1295525 34.296 < 2e-16 ***
ORIGIN_GRID_ID1419 3.9118693 0.1296454 30.174 < 2e-16 ***
ORIGIN_GRID_ID1422 5.1907235 0.1295450 40.069 < 2e-16 ***
ORIGIN_GRID_ID1423 5.9289748 0.1295046 45.782 < 2e-16 ***
ORIGIN_GRID_ID1430 3.4829757 0.1296240 26.870 < 2e-16 ***
ORIGIN_GRID_ID1431 3.4528444 0.1295738 26.648 < 2e-16 ***
ORIGIN_GRID_ID1432 3.5778340 0.1295630 27.615 < 2e-16 ***
ORIGIN_GRID_ID1433 2.3185337 0.1307312 17.735 < 2e-16 ***
ORIGIN_GRID_ID1434 3.8567830 0.1295829 29.763 < 2e-16 ***
ORIGIN_GRID_ID1435 4.2598222 0.1295201 32.889 < 2e-16 ***
ORIGIN_GRID_ID1436 1.1282625 0.1320539 8.544 < 2e-16 ***
ORIGIN_GRID_ID1437 4.4381061 0.1295348 34.262 < 2e-16 ***
ORIGIN_GRID_ID1438 4.9291181 0.1294974 38.063 < 2e-16 ***
ORIGIN_GRID_ID1439 5.5235412 0.1294878 42.657 < 2e-16 ***
ORIGIN_GRID_ID1440 1.9719231 0.1312132 15.028 < 2e-16 ***
ORIGIN_GRID_ID1442 4.9130678 0.1296289 37.901 < 2e-16 ***
ORIGIN_GRID_ID1443 5.8750094 0.1295111 45.363 < 2e-16 ***
ORIGIN_GRID_ID1444 4.9275158 0.1296955 37.993 < 2e-16 ***
ORIGIN_GRID_ID1452 2.5658937 0.1297777 19.771 < 2e-16 ***
ORIGIN_GRID_ID1453 2.6987476 0.1297495 20.800 < 2e-16 ***
ORIGIN_GRID_ID1454 1.8027177 0.1311458 13.746 < 2e-16 ***
ORIGIN_GRID_ID1455 3.2188191 0.1297731 24.803 < 2e-16 ***
ORIGIN_GRID_ID1456 3.6257015 0.1296119 27.974 < 2e-16 ***
ORIGIN_GRID_ID1457 4.4955229 0.1295215 34.709 < 2e-16 ***
ORIGIN_GRID_ID1458 4.8309422 0.1295063 37.303 < 2e-16 ***
ORIGIN_GRID_ID1459 4.2743912 0.1295421 32.996 < 2e-16 ***
ORIGIN_GRID_ID1460 3.4660421 0.1296392 26.736 < 2e-16 ***
ORIGIN_GRID_ID1461 2.1188770 0.1306983 16.212 < 2e-16 ***
ORIGIN_GRID_ID1464 6.3552325 0.1295014 49.075 < 2e-16 ***
ORIGIN_GRID_ID1465 5.8689798 0.1295394 45.307 < 2e-16 ***
ORIGIN_GRID_ID1472 1.1353881 0.1315604 8.630 < 2e-16 ***
ORIGIN_GRID_ID1473 2.0996297 0.1299787 16.154 < 2e-16 ***
ORIGIN_GRID_ID1474 3.2703973 0.1295921 25.236 < 2e-16 ***
ORIGIN_GRID_ID1475 4.2435036 0.1295314 32.760 < 2e-16 ***
ORIGIN_GRID_ID1476 3.5916630 0.1296316 27.707 < 2e-16 ***
ORIGIN_GRID_ID1477 5.1416893 0.1294806 39.710 < 2e-16 ***
ORIGIN_GRID_ID1478 3.4599893 0.1296325 26.691 < 2e-16 ***
ORIGIN_GRID_ID1479 3.6893905 0.1295951 28.469 < 2e-16 ***
ORIGIN_GRID_ID1480 5.5132787 0.1294790 42.580 < 2e-16 ***
ORIGIN_GRID_ID1481 2.8520157 0.1298919 21.957 < 2e-16 ***
ORIGIN_GRID_ID1482 3.0685641 0.1302162 23.565 < 2e-16 ***
ORIGIN_GRID_ID1485 5.8298424 0.1295438 45.003 < 2e-16 ***
ORIGIN_GRID_ID1494 2.3357836 0.1302453 17.934 < 2e-16 ***
ORIGIN_GRID_ID1495 2.5787046 0.1297655 19.872 < 2e-16 ***
ORIGIN_GRID_ID1496 3.7217812 0.1295480 28.729 < 2e-16 ***
ORIGIN_GRID_ID1497 4.0702978 0.1295651 31.415 < 2e-16 ***
ORIGIN_GRID_ID1498 4.4293240 0.1295192 34.198 < 2e-16 ***
ORIGIN_GRID_ID1499 4.6686106 0.1295040 36.050 < 2e-16 ***
ORIGIN_GRID_ID1500 4.5700351 0.1295722 35.270 < 2e-16 ***
ORIGIN_GRID_ID1501 4.8091916 0.1295056 37.135 < 2e-16 ***
ORIGIN_GRID_ID1502 4.2559700 0.1295458 32.853 < 2e-16 ***
ORIGIN_GRID_ID1506 0.4057317 0.1685004 2.408 0.016045 *
ORIGIN_GRID_ID1515 1.5108636 0.1320452 11.442 < 2e-16 ***
ORIGIN_GRID_ID1516 2.9636541 0.1296894 22.852 < 2e-16 ***
ORIGIN_GRID_ID1517 3.4479817 0.1296550 26.594 < 2e-16 ***
ORIGIN_GRID_ID1518 3.3520745 0.1296873 25.847 < 2e-16 ***
ORIGIN_GRID_ID1519 4.7023556 0.1295513 36.297 < 2e-16 ***
ORIGIN_GRID_ID1520 3.4030171 0.1296516 26.247 < 2e-16 ***
ORIGIN_GRID_ID1521 2.7452198 0.1299260 21.129 < 2e-16 ***
ORIGIN_GRID_ID1522 5.0149195 0.1294982 38.726 < 2e-16 ***
ORIGIN_GRID_ID1523 3.5060794 0.1304724 26.872 < 2e-16 ***
ORIGIN_GRID_ID1524 3.6799014 0.1298414 28.342 < 2e-16 ***
ORIGIN_GRID_ID1527 3.6871961 0.1304954 28.255 < 2e-16 ***
ORIGIN_GRID_ID1535 -0.0137562 0.1641479 -0.084 0.933212
ORIGIN_GRID_ID1536 0.8637821 0.1342040 6.436 1.22e-10 ***
ORIGIN_GRID_ID1537 1.5609346 0.1310447 11.911 < 2e-16 ***
ORIGIN_GRID_ID1538 3.1932128 0.1296297 24.633 < 2e-16 ***
ORIGIN_GRID_ID1539 3.7282786 0.1295621 28.776 < 2e-16 ***
ORIGIN_GRID_ID1540 4.3241653 0.1295253 33.385 < 2e-16 ***
ORIGIN_GRID_ID1541 5.5191396 0.1295695 42.596 < 2e-16 ***
ORIGIN_GRID_ID1542 2.4658804 0.1304548 18.902 < 2e-16 ***
ORIGIN_GRID_ID1543 3.2941920 0.1314451 25.061 < 2e-16 ***
ORIGIN_GRID_ID1544 4.2644803 0.1296270 32.898 < 2e-16 ***
ORIGIN_GRID_ID1547 1.4745722 0.1427382 10.331 < 2e-16 ***
ORIGIN_GRID_ID1556 1.1270159 0.1488299 7.573 3.66e-14 ***
ORIGIN_GRID_ID1557 0.8756098 0.1347935 6.496 8.25e-11 ***
ORIGIN_GRID_ID1558 2.1169060 0.1311069 16.146 < 2e-16 ***
ORIGIN_GRID_ID1559 3.8526227 0.1295494 29.739 < 2e-16 ***
ORIGIN_GRID_ID1560 4.7008372 0.1295019 36.299 < 2e-16 ***
ORIGIN_GRID_ID1561 4.5673581 0.1295336 35.260 < 2e-16 ***
ORIGIN_GRID_ID1562 1.6294586 0.1312267 12.417 < 2e-16 ***
ORIGIN_GRID_ID1563 3.4468772 0.1296717 26.582 < 2e-16 ***
ORIGIN_GRID_ID1564 2.6069473 0.1302137 20.021 < 2e-16 ***
ORIGIN_GRID_ID1565 2.6692316 0.1302608 20.491 < 2e-16 ***
ORIGIN_GRID_ID1566 2.4201575 0.1310899 18.462 < 2e-16 ***
ORIGIN_GRID_ID1567 0.3503920 0.1605544 2.182 0.029081 *
ORIGIN_GRID_ID1568 1.2642296 0.1460773 8.655 < 2e-16 ***
ORIGIN_GRID_ID1578 -1.5696643 0.2899357 -5.414 6.17e-08 ***
ORIGIN_GRID_ID1580 2.3270422 0.1306471 17.812 < 2e-16 ***
ORIGIN_GRID_ID1581 1.1660986 0.1312971 8.881 < 2e-16 ***
ORIGIN_GRID_ID1582 4.3913165 0.1295094 33.907 < 2e-16 ***
ORIGIN_GRID_ID1583 2.6556784 0.1312357 20.236 < 2e-16 ***
ORIGIN_GRID_ID1584 2.9308607 0.1299112 22.560 < 2e-16 ***
ORIGIN_GRID_ID1585 3.5580762 0.1298273 27.406 < 2e-16 ***
ORIGIN_GRID_ID1586 2.5475992 0.1301935 19.568 < 2e-16 ***
ORIGIN_GRID_ID1589 0.4282489 0.1608084 2.663 0.007742 **
ORIGIN_GRID_ID1590 1.2295006 0.1447428 8.494 < 2e-16 ***
ORIGIN_GRID_ID1600 4.4446514 0.1298995 34.216 < 2e-16 ***
ORIGIN_GRID_ID1601 2.9883340 0.1296961 23.041 < 2e-16 ***
ORIGIN_GRID_ID1602 3.6704652 0.1296046 28.320 < 2e-16 ***
ORIGIN_GRID_ID1603 4.5798227 0.1295133 35.362 < 2e-16 ***
ORIGIN_GRID_ID1604 3.0978118 0.1297133 23.882 < 2e-16 ***
ORIGIN_GRID_ID1605 4.5082006 0.1295213 34.807 < 2e-16 ***
ORIGIN_GRID_ID1606 3.9846435 0.1298313 30.691 < 2e-16 ***
ORIGIN_GRID_ID1607 3.3084788 0.1298164 25.486 < 2e-16 ***
ORIGIN_GRID_ID1608 5.3175798 0.1295287 41.053 < 2e-16 ***
ORIGIN_GRID_ID1609 5.1932373 0.1295783 40.078 < 2e-16 ***
ORIGIN_GRID_ID1610 1.7974464 0.1457124 12.336 < 2e-16 ***
ORIGIN_GRID_ID1622 3.0546145 0.1314429 23.239 < 2e-16 ***
ORIGIN_GRID_ID1623 4.3708011 0.1295153 33.747 < 2e-16 ***
ORIGIN_GRID_ID1624 3.1454227 0.1297287 24.246 < 2e-16 ***
ORIGIN_GRID_ID1625 4.5396117 0.1295356 35.045 < 2e-16 ***
ORIGIN_GRID_ID1626 5.2119124 0.1294915 40.249 < 2e-16 ***
ORIGIN_GRID_ID1627 3.6005715 0.1296611 27.769 < 2e-16 ***
ORIGIN_GRID_ID1628 5.3442840 0.1294944 41.270 < 2e-16 ***
ORIGIN_GRID_ID1629 4.3509824 0.1296319 33.564 < 2e-16 ***
ORIGIN_GRID_ID1630 4.4901251 0.1296855 34.623 < 2e-16 ***
ORIGIN_GRID_ID1631 0.7924822 0.1471991 5.384 7.30e-08 ***
ORIGIN_GRID_ID1642 1.8647874 0.1330305 14.018 < 2e-16 ***
ORIGIN_GRID_ID1643 4.3280735 0.1295262 33.415 < 2e-16 ***
ORIGIN_GRID_ID1644 2.1086712 0.1305972 16.146 < 2e-16 ***
ORIGIN_GRID_ID1645 3.5727527 0.1296039 27.567 < 2e-16 ***
ORIGIN_GRID_ID1646 3.4154361 0.1297862 26.316 < 2e-16 ***
ORIGIN_GRID_ID1647 3.7945875 0.1295883 29.282 < 2e-16 ***
ORIGIN_GRID_ID1648 4.4423566 0.1295412 34.293 < 2e-16 ***
ORIGIN_GRID_ID1649 5.2243326 0.1295014 40.342 < 2e-16 ***
ORIGIN_GRID_ID1650 5.3411124 0.1295616 41.225 < 2e-16 ***
ORIGIN_GRID_ID1664 -0.7651793 0.1962777 -3.898 9.68e-05 ***
ORIGIN_GRID_ID1665 4.5031360 0.1295112 34.770 < 2e-16 ***
ORIGIN_GRID_ID1666 3.1916759 0.1296610 24.616 < 2e-16 ***
ORIGIN_GRID_ID1667 4.1939263 0.1299062 32.284 < 2e-16 ***
ORIGIN_GRID_ID1668 4.3460723 0.1295374 33.551 < 2e-16 ***
ORIGIN_GRID_ID1670 5.2408225 0.1294946 40.471 < 2e-16 ***
ORIGIN_GRID_ID1671 5.9624844 0.1295571 46.022 < 2e-16 ***
ORIGIN_GRID_ID1672 5.6379651 0.1295833 43.508 < 2e-16 ***
ORIGIN_GRID_ID1684 3.4706826 0.1301710 26.662 < 2e-16 ***
ORIGIN_GRID_ID1685 4.0713375 0.1295644 31.423 < 2e-16 ***
ORIGIN_GRID_ID1686 3.9308005 0.1295680 30.338 < 2e-16 ***
ORIGIN_GRID_ID1687 3.5146540 0.1296799 27.103 < 2e-16 ***
ORIGIN_GRID_ID1688 3.0516644 0.1297577 23.518 < 2e-16 ***
ORIGIN_GRID_ID1689 2.6525221 0.1301497 20.381 < 2e-16 ***
ORIGIN_GRID_ID1690 4.1700158 0.1296221 32.171 < 2e-16 ***
ORIGIN_GRID_ID1691 4.9592794 0.1295262 38.288 < 2e-16 ***
ORIGIN_GRID_ID1692 4.5498136 0.1297226 35.073 < 2e-16 ***
ORIGIN_GRID_ID1706 4.0056840 0.1296179 30.904 < 2e-16 ***
ORIGIN_GRID_ID1707 3.9601807 0.1295518 30.568 < 2e-16 ***
ORIGIN_GRID_ID1708 4.4652471 0.1295157 34.476 < 2e-16 ***
ORIGIN_GRID_ID1709 3.6145253 0.1296255 27.884 < 2e-16 ***
ORIGIN_GRID_ID1710 4.7880815 0.1295195 36.968 < 2e-16 ***
ORIGIN_GRID_ID1711 4.5322725 0.1295571 34.983 < 2e-16 ***
ORIGIN_GRID_ID1712 5.2183917 0.1294952 40.298 < 2e-16 ***
ORIGIN_GRID_ID1713 2.8458812 0.1301606 21.864 < 2e-16 ***
ORIGIN_GRID_ID1714 5.5243094 0.1295387 42.646 < 2e-16 ***
ORIGIN_GRID_ID1727 4.2645692 0.1295640 32.915 < 2e-16 ***
ORIGIN_GRID_ID1728 4.0771651 0.1295484 31.472 < 2e-16 ***
ORIGIN_GRID_ID1729 3.5434276 0.1295900 27.343 < 2e-16 ***
ORIGIN_GRID_ID1730 1.5862593 0.1315229 12.061 < 2e-16 ***
ORIGIN_GRID_ID1731 4.3856348 0.1295566 33.851 < 2e-16 ***
ORIGIN_GRID_ID1732 4.9034541 0.1295050 37.863 < 2e-16 ***
ORIGIN_GRID_ID1733 4.7045669 0.1295305 36.320 < 2e-16 ***
ORIGIN_GRID_ID1734 5.1350319 0.1295238 39.645 < 2e-16 ***
ORIGIN_GRID_ID1735 6.8701857 0.1296240 53.001 < 2e-16 ***
ORIGIN_GRID_ID1748 2.9331304 0.1298762 22.584 < 2e-16 ***
ORIGIN_GRID_ID1749 3.9010949 0.1295589 30.111 < 2e-16 ***
ORIGIN_GRID_ID1750 3.0543826 0.1296893 23.552 < 2e-16 ***
ORIGIN_GRID_ID1751 2.4455252 0.1299433 18.820 < 2e-16 ***
ORIGIN_GRID_ID1753 4.9698796 0.1295094 38.375 < 2e-16 ***
ORIGIN_GRID_ID1754 5.3286158 0.1294927 41.150 < 2e-16 ***
ORIGIN_GRID_ID1755 4.8888194 0.1295265 37.744 < 2e-16 ***
ORIGIN_GRID_ID1756 4.8370074 0.1295677 37.332 < 2e-16 ***
ORIGIN_GRID_ID1757 2.8486234 0.1338268 21.286 < 2e-16 ***
ORIGIN_GRID_ID1769 3.7823262 0.1296048 29.184 < 2e-16 ***
ORIGIN_GRID_ID1770 3.3783495 0.1298919 26.009 < 2e-16 ***
ORIGIN_GRID_ID1771 2.5099316 0.1299644 19.312 < 2e-16 ***
ORIGIN_GRID_ID1772 1.2944247 0.1322665 9.786 < 2e-16 ***
ORIGIN_GRID_ID1774 4.6807523 0.1295242 36.138 < 2e-16 ***
ORIGIN_GRID_ID1775 4.3525107 0.1295752 33.591 < 2e-16 ***
ORIGIN_GRID_ID1776 5.5378079 0.1294966 42.764 < 2e-16 ***
ORIGIN_GRID_ID1777 5.6209522 0.1295120 43.401 < 2e-16 ***
ORIGIN_GRID_ID1778 5.4195532 0.1300656 41.668 < 2e-16 ***
ORIGIN_GRID_ID1790 4.4435488 0.1295541 34.299 < 2e-16 ***
ORIGIN_GRID_ID1791 3.7870737 0.1296306 29.214 < 2e-16 ***
ORIGIN_GRID_ID1792 3.7840483 0.1296475 29.187 < 2e-16 ***
ORIGIN_GRID_ID1793 1.6267648 0.1304198 12.473 < 2e-16 ***
ORIGIN_GRID_ID1794 1.5882168 0.1326479 11.973 < 2e-16 ***
ORIGIN_GRID_ID1795 1.1686948 0.1339541 8.725 < 2e-16 ***
ORIGIN_GRID_ID1796 5.1972578 0.1295253 40.125 < 2e-16 ***
ORIGIN_GRID_ID1797 5.2013854 0.1295111 40.162 < 2e-16 ***
ORIGIN_GRID_ID1798 5.2566291 0.1295118 40.588 < 2e-16 ***
ORIGIN_GRID_ID1799 4.5147588 0.1296857 34.813 < 2e-16 ***
ORIGIN_GRID_ID1800 3.8495978 0.1324740 29.059 < 2e-16 ***
ORIGIN_GRID_ID1811 3.5366919 0.1296885 27.271 < 2e-16 ***
ORIGIN_GRID_ID1812 4.6854831 0.1295031 36.180 < 2e-16 ***
ORIGIN_GRID_ID1813 4.4855767 0.1295128 34.634 < 2e-16 ***
ORIGIN_GRID_ID1817 5.0996855 0.1295646 39.360 < 2e-16 ***
ORIGIN_GRID_ID1818 5.0498663 0.1295323 38.985 < 2e-16 ***
ORIGIN_GRID_ID1819 5.5615999 0.1295057 42.945 < 2e-16 ***
ORIGIN_GRID_ID1820 2.7778261 0.1346185 20.635 < 2e-16 ***
ORIGIN_GRID_ID1832 4.2201155 0.1295780 32.568 < 2e-16 ***
ORIGIN_GRID_ID1833 3.7674836 0.1296026 29.070 < 2e-16 ***
ORIGIN_GRID_ID1834 4.1154723 0.1295355 31.771 < 2e-16 ***
ORIGIN_GRID_ID1835 3.4024728 0.1296835 26.237 < 2e-16 ***
ORIGIN_GRID_ID1837 0.6513357 0.1440760 4.521 6.16e-06 ***
ORIGIN_GRID_ID1839 4.5180314 0.1296651 34.844 < 2e-16 ***
ORIGIN_GRID_ID1840 6.3125265 0.1294808 48.753 < 2e-16 ***
ORIGIN_GRID_ID1841 1.8212907 0.1374000 13.255 < 2e-16 ***
ORIGIN_GRID_ID1842 6.2821807 0.1299695 48.336 < 2e-16 ***
ORIGIN_GRID_ID1853 4.1807762 0.1295527 32.271 < 2e-16 ***
ORIGIN_GRID_ID1854 4.3748977 0.1295428 33.772 < 2e-16 ***
ORIGIN_GRID_ID1855 4.6848624 0.1295214 36.171 < 2e-16 ***
ORIGIN_GRID_ID1858 2.4700359 0.1322723 18.674 < 2e-16 ***
ORIGIN_GRID_ID1860 5.8440973 0.1297590 45.038 < 2e-16 ***
ORIGIN_GRID_ID1861 5.3098588 0.1295371 40.991 < 2e-16 ***
ORIGIN_GRID_ID1874 4.3344626 0.1296108 33.442 < 2e-16 ***
ORIGIN_GRID_ID1875 2.6940666 0.1301830 20.694 < 2e-16 ***
ORIGIN_GRID_ID1876 4.7585856 0.1299295 36.624 < 2e-16 ***
ORIGIN_GRID_ID1877 4.4033634 0.1295446 33.991 < 2e-16 ***
ORIGIN_GRID_ID1880 0.8468867 0.1385141 6.114 9.71e-10 ***
ORIGIN_GRID_ID1882 5.1502051 0.1295496 39.755 < 2e-16 ***
ORIGIN_GRID_ID1883 5.6606459 0.1297862 43.615 < 2e-16 ***
ORIGIN_GRID_ID1895 4.4672434 0.1295443 34.484 < 2e-16 ***
ORIGIN_GRID_ID1896 2.8483715 0.1298433 21.937 < 2e-16 ***
ORIGIN_GRID_ID1897 3.4819052 0.1297939 26.826 < 2e-16 ***
ORIGIN_GRID_ID1898 -0.8986596 0.1987260 -4.522 6.12e-06 ***
ORIGIN_GRID_ID1901 0.7166187 0.1483570 4.830 1.36e-06 ***
ORIGIN_GRID_ID1903 5.0598976 0.1297727 38.990 < 2e-16 ***
ORIGIN_GRID_ID1917 2.9908180 0.1298440 23.034 < 2e-16 ***
ORIGIN_GRID_ID1918 4.5109737 0.1295928 34.809 < 2e-16 ***
ORIGIN_GRID_ID1919 4.3720565 0.1295619 33.745 < 2e-16 ***
ORIGIN_GRID_ID1922 2.2174112 0.1325019 16.735 < 2e-16 ***
ORIGIN_GRID_ID1924 4.8713952 0.1298136 37.526 < 2e-16 ***
ORIGIN_GRID_ID1937 3.8176502 0.1296549 29.445 < 2e-16 ***
ORIGIN_GRID_ID1938 4.5150133 0.1295303 34.857 < 2e-16 ***
ORIGIN_GRID_ID1939 5.1029870 0.1295185 39.400 < 2e-16 ***
ORIGIN_GRID_ID1942 1.0378011 0.1374710 7.549 4.38e-14 ***
ORIGIN_GRID_ID1959 3.4192921 0.1297712 26.349 < 2e-16 ***
ORIGIN_GRID_ID1960 5.3933530 0.1294828 41.653 < 2e-16 ***
ORIGIN_GRID_ID1961 3.8302715 0.1296519 29.543 < 2e-16 ***
ORIGIN_GRID_ID1962 4.8744402 0.1295257 37.633 < 2e-16 ***
ORIGIN_GRID_ID1964 0.1951234 0.1555266 1.255 0.209625
ORIGIN_GRID_ID1979 3.7144527 0.1297220 28.634 < 2e-16 ***
ORIGIN_GRID_ID1980 2.0391014 0.1303063 15.649 < 2e-16 ***
ORIGIN_GRID_ID1981 4.5094962 0.1295273 34.815 < 2e-16 ***
ORIGIN_GRID_ID1982 3.5160981 0.1299771 27.052 < 2e-16 ***
ORIGIN_GRID_ID1983 4.7850784 0.1295290 36.942 < 2e-16 ***
ORIGIN_GRID_ID1984 3.4819864 0.1297034 26.846 < 2e-16 ***
ORIGIN_GRID_ID1985 4.2753701 0.1296116 32.986 < 2e-16 ***
ORIGIN_GRID_ID2001 4.0224288 0.1295971 31.038 < 2e-16 ***
ORIGIN_GRID_ID2002 4.5950943 0.1295096 35.481 < 2e-16 ***
ORIGIN_GRID_ID2003 4.2499253 0.1295563 32.804 < 2e-16 ***
ORIGIN_GRID_ID2004 4.8509741 0.1295251 37.452 < 2e-16 ***
ORIGIN_GRID_ID2005 4.7564195 0.1295202 36.723 < 2e-16 ***
ORIGIN_GRID_ID2006 3.2909912 0.1298202 25.350 < 2e-16 ***
ORIGIN_GRID_ID2007 2.7471672 0.1305356 21.045 < 2e-16 ***
ORIGIN_GRID_ID2022 4.3799548 0.1296004 33.796 < 2e-16 ***
ORIGIN_GRID_ID2023 4.8576326 0.1295063 37.509 < 2e-16 ***
ORIGIN_GRID_ID2024 4.1567495 0.1295463 32.087 < 2e-16 ***
ORIGIN_GRID_ID2025 4.2244761 0.1295389 32.612 < 2e-16 ***
ORIGIN_GRID_ID2026 2.9274015 0.1300125 22.516 < 2e-16 ***
ORIGIN_GRID_ID2027 5.1652141 0.1295149 39.881 < 2e-16 ***
ORIGIN_GRID_ID2043 3.7360782 0.1296998 28.806 < 2e-16 ***
ORIGIN_GRID_ID2044 4.4653641 0.1295245 34.475 < 2e-16 ***
ORIGIN_GRID_ID2045 -0.0143942 0.1514502 -0.095 0.924281
ORIGIN_GRID_ID2046 4.4043491 0.1295140 34.007 < 2e-16 ***
ORIGIN_GRID_ID2047 4.2409705 0.1295632 32.733 < 2e-16 ***
ORIGIN_GRID_ID2048 4.4870139 0.1295382 34.639 < 2e-16 ***
ORIGIN_GRID_ID2049 3.5662488 0.1302043 27.390 < 2e-16 ***
ORIGIN_GRID_ID2064 4.4353047 0.1295533 34.235 < 2e-16 ***
ORIGIN_GRID_ID2065 2.8815924 0.1297655 22.206 < 2e-16 ***
ORIGIN_GRID_ID2066 2.2495968 0.1319800 17.045 < 2e-16 ***
ORIGIN_GRID_ID2067 5.6572006 0.1294790 43.692 < 2e-16 ***
ORIGIN_GRID_ID2068 4.0445849 0.1296509 31.196 < 2e-16 ***
ORIGIN_GRID_ID2069 4.3657257 0.1295757 33.692 < 2e-16 ***
ORIGIN_GRID_ID2085 3.3026684 0.1298421 25.436 < 2e-16 ***
ORIGIN_GRID_ID2086 4.7337277 0.1295191 36.548 < 2e-16 ***
ORIGIN_GRID_ID2087 3.3469174 0.1296799 25.809 < 2e-16 ***
ORIGIN_GRID_ID2088 4.0743694 0.1295400 31.453 < 2e-16 ***
ORIGIN_GRID_ID2089 3.8549098 0.1296261 29.739 < 2e-16 ***
ORIGIN_GRID_ID2090 5.3530167 0.1294982 41.337 < 2e-16 ***
ORIGIN_GRID_ID2091 0.6350794 0.1490976 4.259 2.05e-05 ***
ORIGIN_GRID_ID2105 1.3690447 0.1729854 7.914 2.49e-15 ***
ORIGIN_GRID_ID2106 1.6435398 0.1310460 12.542 < 2e-16 ***
ORIGIN_GRID_ID2107 2.7515870 0.1298210 21.195 < 2e-16 ***
ORIGIN_GRID_ID2108 4.0312654 0.1295816 31.110 < 2e-16 ***
ORIGIN_GRID_ID2109 4.1435236 0.1295357 31.988 < 2e-16 ***
ORIGIN_GRID_ID2110 3.5914328 0.1296740 27.696 < 2e-16 ***
ORIGIN_GRID_ID2111 0.6827934 0.1387074 4.923 8.54e-07 ***
ORIGIN_GRID_ID2128 2.4407853 0.1303441 18.726 < 2e-16 ***
ORIGIN_GRID_ID2129 1.8892312 0.1304780 14.479 < 2e-16 ***
ORIGIN_GRID_ID2130 4.5991720 0.1295120 35.512 < 2e-16 ***
ORIGIN_GRID_ID2131 4.9344596 0.1295346 38.094 < 2e-16 ***
ORIGIN_GRID_ID2132 3.8607399 0.1296046 29.789 < 2e-16 ***
ORIGIN_GRID_ID2148 3.3586508 0.1300198 25.832 < 2e-16 ***
ORIGIN_GRID_ID2149 1.9202201 0.1305429 14.709 < 2e-16 ***
ORIGIN_GRID_ID2150 4.4747519 0.1295395 34.544 < 2e-16 ***
ORIGIN_GRID_ID2151 4.9520741 0.1295004 38.240 < 2e-16 ***
ORIGIN_GRID_ID2152 5.1252857 0.1295085 39.575 < 2e-16 ***
ORIGIN_GRID_ID2153 4.4780224 0.1295767 34.559 < 2e-16 ***
ORIGIN_GRID_ID2171 3.4614431 0.1296761 26.693 < 2e-16 ***
ORIGIN_GRID_ID2172 3.5921648 0.1297092 27.694 < 2e-16 ***
ORIGIN_GRID_ID2173 4.1277056 0.1295583 31.860 < 2e-16 ***
ORIGIN_GRID_ID2174 4.4050143 0.1295667 33.998 < 2e-16 ***
ORIGIN_GRID_ID2191 3.1080217 0.1299204 23.922 < 2e-16 ***
ORIGIN_GRID_ID2192 2.8512432 0.1299864 21.935 < 2e-16 ***
ORIGIN_GRID_ID2193 3.7810669 0.1296124 29.172 < 2e-16 ***
ORIGIN_GRID_ID2194 4.2254067 0.1295605 32.613 < 2e-16 ***
ORIGIN_GRID_ID2195 3.5970382 0.1313635 27.382 < 2e-16 ***
ORIGIN_GRID_ID2212 0.3513632 0.1659159 2.118 0.034199 *
ORIGIN_GRID_ID2213 0.7250896 0.1369898 5.293 1.20e-07 ***
ORIGIN_GRID_ID2214 1.2979397 0.1325044 9.795 < 2e-16 ***
ORIGIN_GRID_ID2215 3.8577960 0.1296547 29.754 < 2e-16 ***
ORIGIN_GRID_ID2216 2.8797110 0.1299567 22.159 < 2e-16 ***
ORIGIN_GRID_ID2233 0.9722065 0.1386183 7.014 2.32e-12 ***
ORIGIN_GRID_ID2234 2.6991471 0.1311508 20.580 < 2e-16 ***
ORIGIN_GRID_ID2235 2.6523287 0.1302287 20.367 < 2e-16 ***
ORIGIN_GRID_ID2236 2.6689875 0.1301238 20.511 < 2e-16 ***
ORIGIN_GRID_ID2237 0.3896868 0.1434759 2.716 0.006607 **
ORIGIN_GRID_ID2256 0.4057209 0.1369433 2.963 0.003050 **
ORIGIN_GRID_ID2257 2.4104485 0.1310721 18.390 < 2e-16 ***
ORIGIN_GRID_ID2258 1.9412589 0.1305367 14.871 < 2e-16 ***
ORIGIN_GRID_ID2259 1.4218246 0.1354665 10.496 < 2e-16 ***
ORIGIN_GRID_ID2277 2.5921467 0.1350162 19.199 < 2e-16 ***
ORIGIN_GRID_ID2278 2.9840065 0.1304961 22.867 < 2e-16 ***
ORIGIN_GRID_ID2279 1.5580820 0.1311136 11.883 < 2e-16 ***
ORIGIN_GRID_ID2280 -0.6682589 0.1861251 -3.590 0.000330 ***
ORIGIN_GRID_ID2297 4.3996436 0.1298243 33.889 < 2e-16 ***
ORIGIN_GRID_ID2300 0.2825226 0.1471284 1.920 0.054827 .
ORIGIN_GRID_ID2301 1.8871756 0.1310241 14.403 < 2e-16 ***
ORIGIN_GRID_ID2318 2.4844203 0.1309715 18.969 < 2e-16 ***
ORIGIN_GRID_ID2319 3.0876630 0.1299704 23.757 < 2e-16 ***
ORIGIN_GRID_ID2322 2.9883089 0.1301146 22.967 < 2e-16 ***
ORIGIN_GRID_ID2337 4.0335768 0.1307038 30.860 < 2e-16 ***
ORIGIN_GRID_ID2341 3.4571939 0.1298977 26.615 < 2e-16 ***
ORIGIN_GRID_ID2343 2.3037361 0.1303076 17.679 < 2e-16 ***
ORIGIN_GRID_ID2361 3.1777032 0.1301040 24.424 < 2e-16 ***
ORIGIN_GRID_ID2364 -0.9479956 0.1610691 -5.886 3.97e-09 ***
ORIGIN_GRID_ID2379 3.4107526 0.1311009 26.016 < 2e-16 ***
ORIGIN_GRID_ID2384 2.0474549 0.1306598 15.670 < 2e-16 ***
ORIGIN_GRID_ID2405 1.6786496 0.1308066 12.833 < 2e-16 ***
ORIGIN_GRID_ID2406 0.4317805 0.1355121 3.186 0.001441 **
ORIGIN_GRID_ID2426 1.1570505 0.1337346 8.652 < 2e-16 ***
ORIGIN_GRID_ID2427 2.9864567 0.1300117 22.971 < 2e-16 ***
ORIGIN_GRID_ID2505 3.2462592 0.1375541 23.600 < 2e-16 ***
DESTIN_GRID_ID44 1.4624860 0.0599514 24.395 < 2e-16 ***
DESTIN_GRID_ID46 0.5331682 0.0595107 8.959 < 2e-16 ***
DESTIN_GRID_ID66 -0.3320008 0.0737212 -4.503 6.69e-06 ***
DESTIN_GRID_ID67 0.4696417 0.0576872 8.141 3.91e-16 ***
DESTIN_GRID_ID68 0.1786194 0.0596421 2.995 0.002746 **
DESTIN_GRID_ID86 0.5441985 0.0661281 8.229 < 2e-16 ***
DESTIN_GRID_ID87 -2.8315043 0.1051530 -26.927 < 2e-16 ***
DESTIN_GRID_ID88 -0.0308727 0.0586923 -0.526 0.598882
DESTIN_GRID_ID89 -0.5611009 0.0601853 -9.323 < 2e-16 ***
DESTIN_GRID_ID90 -3.6891307 0.7095098 -5.200 2.00e-07 ***
DESTIN_GRID_ID109 -0.3506186 0.0610845 -5.740 9.47e-09 ***
DESTIN_GRID_ID110 -3.3021726 0.1302716 -25.348 < 2e-16 ***
DESTIN_GRID_ID111 1.1174823 0.0570266 19.596 < 2e-16 ***
DESTIN_GRID_ID112 -2.3544255 0.0649359 -36.258 < 2e-16 ***
DESTIN_GRID_ID128 1.2002220 0.0610706 19.653 < 2e-16 ***
DESTIN_GRID_ID129 -4.2793412 0.1496811 -28.590 < 2e-16 ***
DESTIN_GRID_ID130 -0.5627503 0.0605577 -9.293 < 2e-16 ***
DESTIN_GRID_ID131 -1.2795769 0.0602748 -21.229 < 2e-16 ***
DESTIN_GRID_ID132 -0.7621323 0.0576397 -13.222 < 2e-16 ***
DESTIN_GRID_ID133 -0.6592448 0.0570087 -11.564 < 2e-16 ***
DESTIN_GRID_ID134 -0.5243595 0.0568429 -9.225 < 2e-16 ***
DESTIN_GRID_ID150 -0.1411154 0.0654155 -2.157 0.030989 *
DESTIN_GRID_ID151 -0.4586690 0.0603648 -7.598 3.00e-14 ***
DESTIN_GRID_ID152 0.4913220 0.0578567 8.492 < 2e-16 ***
DESTIN_GRID_ID153 0.0427622 0.0575499 0.743 0.457454
DESTIN_GRID_ID154 -2.1122012 0.0625217 -33.783 < 2e-16 ***
DESTIN_GRID_ID155 -1.7201215 0.0590417 -29.134 < 2e-16 ***
DESTIN_GRID_ID156 -1.5904139 0.0601227 -26.453 < 2e-16 ***
DESTIN_GRID_ID172 -1.5236227 0.0719022 -21.190 < 2e-16 ***
DESTIN_GRID_ID174 -1.0247315 0.0579098 -17.695 < 2e-16 ***
DESTIN_GRID_ID175 -0.6161527 0.0566491 -10.877 < 2e-16 ***
DESTIN_GRID_ID176 -1.9672231 0.0631626 -31.145 < 2e-16 ***
DESTIN_GRID_ID195 -2.3227621 0.0638221 -36.394 < 2e-16 ***
DESTIN_GRID_ID196 -0.8811850 0.0566371 -15.558 < 2e-16 ***
DESTIN_GRID_ID197 -4.0878675 0.0951997 -42.940 < 2e-16 ***
DESTIN_GRID_ID215 -0.3733988 0.0633975 -5.890 3.87e-09 ***
DESTIN_GRID_ID216 -0.5072262 0.0579484 -8.753 < 2e-16 ***
DESTIN_GRID_ID217 -0.1767057 0.0565082 -3.127 0.001766 **
DESTIN_GRID_ID237 -2.4770462 0.0637291 -38.868 < 2e-16 ***
DESTIN_GRID_ID238 -1.4853314 0.0578222 -25.688 < 2e-16 ***
DESTIN_GRID_ID239 -1.7672708 0.0639682 -27.627 < 2e-16 ***
DESTIN_GRID_ID257 0.4761961 0.0582214 8.179 2.86e-16 ***
DESTIN_GRID_ID258 -1.3991486 0.0590879 -23.679 < 2e-16 ***
DESTIN_GRID_ID259 -0.2927528 0.0570379 -5.133 2.86e-07 ***
DESTIN_GRID_ID278 0.8479391 0.0576980 14.696 < 2e-16 ***
DESTIN_GRID_ID279 -0.8762764 0.0574057 -15.265 < 2e-16 ***
DESTIN_GRID_ID280 -0.6161109 0.0572352 -10.765 < 2e-16 ***
DESTIN_GRID_ID298 -3.8322281 0.1608998 -23.817 < 2e-16 ***
DESTIN_GRID_ID299 -0.5900393 0.0581466 -10.147 < 2e-16 ***
DESTIN_GRID_ID300 -1.1629633 0.0584288 -19.904 < 2e-16 ***
DESTIN_GRID_ID320 0.7340106 0.0576168 12.740 < 2e-16 ***
DESTIN_GRID_ID321 -1.5270825 0.0608577 -25.093 < 2e-16 ***
DESTIN_GRID_ID322 -0.2762832 0.0571085 -4.838 1.31e-06 ***
DESTIN_GRID_ID340 1.4463172 0.0569553 25.394 < 2e-16 ***
DESTIN_GRID_ID341 -0.0482526 0.0571570 -0.844 0.398551
DESTIN_GRID_ID342 -0.4018783 0.0568447 -7.070 1.55e-12 ***
DESTIN_GRID_ID363 -0.4163730 0.0574594 -7.246 4.28e-13 ***
DESTIN_GRID_ID364 -0.4112995 0.0564049 -7.292 3.06e-13 ***
DESTIN_GRID_ID383 0.5974695 0.0566147 10.553 < 2e-16 ***
DESTIN_GRID_ID384 -0.6003152 0.0564951 -10.626 < 2e-16 ***
DESTIN_GRID_ID385 -1.5809602 0.0579193 -27.296 < 2e-16 ***
DESTIN_GRID_ID404 0.7285456 0.0572957 12.716 < 2e-16 ***
DESTIN_GRID_ID405 -0.0017707 0.0568760 -0.031 0.975164
DESTIN_GRID_ID406 0.3280441 0.0561270 5.845 5.08e-09 ***
DESTIN_GRID_ID407 -0.1847824 0.0567581 -3.256 0.001131 **
DESTIN_GRID_ID408 0.9904145 0.0561916 17.626 < 2e-16 ***
DESTIN_GRID_ID425 -1.6440794 0.0611844 -26.871 < 2e-16 ***
DESTIN_GRID_ID426 -1.0583495 0.0568109 -18.629 < 2e-16 ***
DESTIN_GRID_ID427 -3.7248399 0.0618368 -60.237 < 2e-16 ***
DESTIN_GRID_ID428 -1.1467855 0.0571893 -20.052 < 2e-16 ***
DESTIN_GRID_ID429 -1.3391768 0.0608720 -22.000 < 2e-16 ***
DESTIN_GRID_ID446 -0.4318361 0.0605220 -7.135 9.67e-13 ***
DESTIN_GRID_ID447 -1.2596929 0.0584551 -21.550 < 2e-16 ***
DESTIN_GRID_ID448 -1.5701739 0.0570775 -27.510 < 2e-16 ***
DESTIN_GRID_ID449 -0.9332641 0.0563922 -16.550 < 2e-16 ***
DESTIN_GRID_ID450 -1.5364440 0.0573840 -26.775 < 2e-16 ***
DESTIN_GRID_ID468 -0.9072318 0.0569309 -15.936 < 2e-16 ***
DESTIN_GRID_ID469 -1.4515501 0.0565701 -25.659 < 2e-16 ***
DESTIN_GRID_ID470 -1.2582098 0.0564309 -22.296 < 2e-16 ***
DESTIN_GRID_ID471 -1.0894808 0.0585887 -18.595 < 2e-16 ***
DESTIN_GRID_ID488 -0.5062734 0.0602372 -8.405 < 2e-16 ***
DESTIN_GRID_ID489 -2.5885207 0.0737436 -35.102 < 2e-16 ***
DESTIN_GRID_ID490 -0.6725338 0.0565731 -11.888 < 2e-16 ***
DESTIN_GRID_ID491 -3.1559150 0.0584053 -54.035 < 2e-16 ***
DESTIN_GRID_ID493 -3.4963758 0.0743152 -47.048 < 2e-16 ***
DESTIN_GRID_ID494 -1.7032307 0.0605704 -28.120 < 2e-16 ***
DESTIN_GRID_ID509 -0.1462624 0.0580336 -2.520 0.011725 *
DESTIN_GRID_ID510 -0.4193651 0.0568415 -7.378 1.61e-13 ***
DESTIN_GRID_ID511 -1.1973548 0.0563539 -21.247 < 2e-16 ***
DESTIN_GRID_ID512 -1.5120772 0.0563833 -26.818 < 2e-16 ***
DESTIN_GRID_ID513 -0.3554135 0.0565768 -6.282 3.34e-10 ***
DESTIN_GRID_ID514 -0.6610144 0.0572302 -11.550 < 2e-16 ***
DESTIN_GRID_ID515 -2.1604997 0.0645532 -33.469 < 2e-16 ***
DESTIN_GRID_ID530 -0.7656944 0.0630718 -12.140 < 2e-16 ***
DESTIN_GRID_ID531 1.4455133 0.0562872 25.681 < 2e-16 ***
DESTIN_GRID_ID532 -0.9559796 0.0566297 -16.881 < 2e-16 ***
DESTIN_GRID_ID533 0.2040941 0.0560218 3.643 0.000269 ***
DESTIN_GRID_ID534 -1.2870480 0.0563845 -22.826 < 2e-16 ***
DESTIN_GRID_ID536 -1.5752232 0.0589064 -26.741 < 2e-16 ***
DESTIN_GRID_ID537 -2.3623086 0.0658865 -35.854 < 2e-16 ***
DESTIN_GRID_ID538 -2.6975159 0.0714045 -37.778 < 2e-16 ***
DESTIN_GRID_ID539 -5.0234153 0.2730826 -18.395 < 2e-16 ***
DESTIN_GRID_ID551 -0.1567306 0.0587428 -2.668 0.007629 **
DESTIN_GRID_ID552 0.2474527 0.0569883 4.342 1.41e-05 ***
DESTIN_GRID_ID553 -1.7199300 0.0566187 -30.377 < 2e-16 ***
DESTIN_GRID_ID554 -1.7918780 0.0564025 -31.770 < 2e-16 ***
DESTIN_GRID_ID555 -0.5435785 0.0564833 -9.624 < 2e-16 ***
DESTIN_GRID_ID559 -2.8145915 0.0775951 -36.273 < 2e-16 ***
DESTIN_GRID_ID560 -0.4783951 0.0584981 -8.178 2.89e-16 ***
DESTIN_GRID_ID561 -2.8617681 0.0877713 -32.605 < 2e-16 ***
DESTIN_GRID_ID572 -1.0743681 0.0657328 -16.344 < 2e-16 ***
DESTIN_GRID_ID573 0.6106059 0.0569365 10.724 < 2e-16 ***
DESTIN_GRID_ID574 -1.2097612 0.0581364 -20.809 < 2e-16 ***
DESTIN_GRID_ID575 1.2344892 0.0559784 22.053 < 2e-16 ***
DESTIN_GRID_ID576 -1.3983694 0.0563246 -24.827 < 2e-16 ***
DESTIN_GRID_ID578 -4.7683512 0.1209514 -39.424 < 2e-16 ***
DESTIN_GRID_ID582 -3.0686695 0.0844682 -36.329 < 2e-16 ***
DESTIN_GRID_ID583 -4.9513051 0.3820977 -12.958 < 2e-16 ***
DESTIN_GRID_ID584 -1.4970629 0.0666719 -22.454 < 2e-16 ***
DESTIN_GRID_ID593 -1.7082441 0.0615412 -27.758 < 2e-16 ***
DESTIN_GRID_ID594 -0.3913954 0.0577024 -6.783 1.18e-11 ***
DESTIN_GRID_ID595 -0.6025499 0.0562620 -10.710 < 2e-16 ***
DESTIN_GRID_ID596 -1.1909728 0.0561843 -21.198 < 2e-16 ***
DESTIN_GRID_ID597 -1.6628591 0.0580974 -28.622 < 2e-16 ***
DESTIN_GRID_ID603 -2.6215172 0.0769874 -34.051 < 2e-16 ***
DESTIN_GRID_ID604 -2.1613105 0.0755892 -28.593 < 2e-16 ***
DESTIN_GRID_ID615 -1.3101238 0.0578812 -22.635 < 2e-16 ***
DESTIN_GRID_ID616 -0.8264494 0.0566977 -14.576 < 2e-16 ***
DESTIN_GRID_ID617 -1.9167467 0.0567100 -33.799 < 2e-16 ***
DESTIN_GRID_ID618 -1.4145140 0.0563655 -25.095 < 2e-16 ***
DESTIN_GRID_ID620 -1.2636786 0.0571270 -22.121 < 2e-16 ***
DESTIN_GRID_ID637 -1.3288022 0.0570320 -23.299 < 2e-16 ***
DESTIN_GRID_ID638 -1.3930781 0.0563036 -24.742 < 2e-16 ***
DESTIN_GRID_ID657 0.0254908 0.0564119 0.452 0.651363
DESTIN_GRID_ID658 -0.6890636 0.0563086 -12.237 < 2e-16 ***
DESTIN_GRID_ID659 -0.9946705 0.0562707 -17.677 < 2e-16 ***
DESTIN_GRID_ID660 -0.5944060 0.0561313 -10.590 < 2e-16 ***
DESTIN_GRID_ID662 -1.1621583 0.0573416 -20.267 < 2e-16 ***
DESTIN_GRID_ID677 0.0875335 0.0567685 1.542 0.123089
DESTIN_GRID_ID678 -1.8246658 0.0577236 -31.610 < 2e-16 ***
DESTIN_GRID_ID679 -0.3980577 0.0561965 -7.083 1.41e-12 ***
DESTIN_GRID_ID680 1.0480997 0.0560162 18.711 < 2e-16 ***
DESTIN_GRID_ID681 -2.8377105 0.0596445 -47.577 < 2e-16 ***
DESTIN_GRID_ID699 -0.4938595 0.0567084 -8.709 < 2e-16 ***
DESTIN_GRID_ID700 -1.0354385 0.0564452 -18.344 < 2e-16 ***
DESTIN_GRID_ID701 -3.5126977 0.0605667 -57.997 < 2e-16 ***
DESTIN_GRID_ID702 -0.8081616 0.0561859 -14.384 < 2e-16 ***
DESTIN_GRID_ID704 -1.6800955 0.0570996 -29.424 < 2e-16 ***
DESTIN_GRID_ID722 -1.5630289 0.0566937 -27.570 < 2e-16 ***
DESTIN_GRID_ID725 -3.8470323 0.0624666 -61.585 < 2e-16 ***
DESTIN_GRID_ID741 0.0562466 0.0564622 0.996 0.319162
DESTIN_GRID_ID743 -3.6849690 0.0612001 -60.212 < 2e-16 ***
DESTIN_GRID_ID744 -0.7445814 0.0561938 -13.250 < 2e-16 ***
DESTIN_GRID_ID761 0.3504692 0.0566360 6.188 6.09e-10 ***
DESTIN_GRID_ID762 -1.7229021 0.0577557 -29.831 < 2e-16 ***
DESTIN_GRID_ID763 -3.3119528 0.0602140 -55.003 < 2e-16 ***
DESTIN_GRID_ID764 -0.2224540 0.0560890 -3.966 7.31e-05 ***
DESTIN_GRID_ID765 -1.0519790 0.0568291 -18.511 < 2e-16 ***
DESTIN_GRID_ID767 -1.3589152 0.0564476 -24.074 < 2e-16 ***
DESTIN_GRID_ID772 -2.3283828 0.0697495 -33.382 < 2e-16 ***
DESTIN_GRID_ID784 -3.1322613 0.0605052 -51.769 < 2e-16 ***
DESTIN_GRID_ID785 -1.1758337 0.0562692 -20.897 < 2e-16 ***
DESTIN_GRID_ID786 -1.0593268 0.0562008 -18.849 < 2e-16 ***
DESTIN_GRID_ID787 -1.8782540 0.0570920 -32.899 < 2e-16 ***
DESTIN_GRID_ID788 -3.3952483 0.0585563 -57.983 < 2e-16 ***
DESTIN_GRID_ID789 -3.5677526 0.0590484 -60.421 < 2e-16 ***
DESTIN_GRID_ID803 -0.8572608 0.0577445 -14.846 < 2e-16 ***
DESTIN_GRID_ID804 -0.3332015 0.0563497 -5.913 3.36e-09 ***
DESTIN_GRID_ID805 0.6065399 0.0560429 10.823 < 2e-16 ***
DESTIN_GRID_ID806 -1.2835970 0.0562847 -22.805 < 2e-16 ***
DESTIN_GRID_ID807 -1.2608901 0.0564795 -22.325 < 2e-16 ***
DESTIN_GRID_ID808 -2.6501936 0.0588321 -45.047 < 2e-16 ***
DESTIN_GRID_ID809 -1.4790081 0.0562576 -26.290 < 2e-16 ***
DESTIN_GRID_ID810 -1.8068946 0.0566396 -31.902 < 2e-16 ***
DESTIN_GRID_ID814 -1.2525046 0.0598518 -20.927 < 2e-16 ***
DESTIN_GRID_ID819 -0.1941675 0.0585576 -3.316 0.000914 ***
DESTIN_GRID_ID824 -0.6405147 0.0577050 -11.100 < 2e-16 ***
DESTIN_GRID_ID826 -0.9388190 0.0563137 -16.671 < 2e-16 ***
DESTIN_GRID_ID827 -1.3084359 0.0563750 -23.210 < 2e-16 ***
DESTIN_GRID_ID828 -1.1406741 0.0562201 -20.289 < 2e-16 ***
DESTIN_GRID_ID829 -1.5945707 0.0566013 -28.172 < 2e-16 ***
DESTIN_GRID_ID830 -3.1182491 0.0579200 -53.837 < 2e-16 ***
DESTIN_GRID_ID831 0.4313444 0.0560445 7.696 1.40e-14 ***
DESTIN_GRID_ID832 0.0509426 0.0561460 0.907 0.364235
DESTIN_GRID_ID835 -1.6826145 0.0599380 -28.073 < 2e-16 ***
DESTIN_GRID_ID844 -0.9204713 0.0590054 -15.600 < 2e-16 ***
DESTIN_GRID_ID846 -0.9825733 0.0564517 -17.406 < 2e-16 ***
DESTIN_GRID_ID847 -0.2538514 0.0561666 -4.520 6.20e-06 ***
DESTIN_GRID_ID848 -1.4929337 0.0563766 -26.481 < 2e-16 ***
DESTIN_GRID_ID849 -2.1418465 0.0566139 -37.833 < 2e-16 ***
DESTIN_GRID_ID850 -1.3040440 0.0562616 -23.178 < 2e-16 ***
DESTIN_GRID_ID851 -1.9160438 0.0563956 -33.975 < 2e-16 ***
DESTIN_GRID_ID852 -1.9695090 0.0566361 -34.775 < 2e-16 ***
DESTIN_GRID_ID853 -0.9781103 0.0567864 -17.224 < 2e-16 ***
DESTIN_GRID_ID854 -0.8988821 0.0578460 -15.539 < 2e-16 ***
DESTIN_GRID_ID855 -1.8452509 0.0596010 -30.960 < 2e-16 ***
DESTIN_GRID_ID856 -2.4637411 0.0647014 -38.079 < 2e-16 ***
DESTIN_GRID_ID866 -0.1421270 0.0568678 -2.499 0.012446 *
DESTIN_GRID_ID867 0.3739560 0.0561640 6.658 2.77e-11 ***
DESTIN_GRID_ID868 -0.1418996 0.0562512 -2.523 0.011649 *
DESTIN_GRID_ID869 0.7682803 0.0562217 13.665 < 2e-16 ***
DESTIN_GRID_ID870 0.2609175 0.0560459 4.655 3.23e-06 ***
DESTIN_GRID_ID871 0.1714895 0.0561271 3.055 0.002248 **
DESTIN_GRID_ID872 -1.4493608 0.0563174 -25.736 < 2e-16 ***
DESTIN_GRID_ID873 -1.9073282 0.0566778 -33.652 < 2e-16 ***
DESTIN_GRID_ID874 -3.1056814 0.0577010 -53.824 < 2e-16 ***
DESTIN_GRID_ID875 -2.3975125 0.0624266 -38.405 < 2e-16 ***
DESTIN_GRID_ID876 -2.0306725 0.0591726 -34.318 < 2e-16 ***
DESTIN_GRID_ID877 -1.4676438 0.0579094 -25.344 < 2e-16 ***
DESTIN_GRID_ID887 -0.9642493 0.0567147 -17.002 < 2e-16 ***
DESTIN_GRID_ID888 -2.2215507 0.0578961 -38.371 < 2e-16 ***
DESTIN_GRID_ID889 -1.4950579 0.0574775 -26.011 < 2e-16 ***
DESTIN_GRID_ID890 -0.6318399 0.0562070 -11.241 < 2e-16 ***
DESTIN_GRID_ID891 -2.1861153 0.0580555 -37.656 < 2e-16 ***
DESTIN_GRID_ID893 -0.9075875 0.0561578 -16.161 < 2e-16 ***
DESTIN_GRID_ID894 -2.4773300 0.0571425 -43.354 < 2e-16 ***
DESTIN_GRID_ID895 -1.2389940 0.0567254 -21.842 < 2e-16 ***
DESTIN_GRID_ID896 -3.6045152 0.0653784 -55.133 < 2e-16 ***
DESTIN_GRID_ID897 -3.7250573 0.0644033 -57.840 < 2e-16 ***
DESTIN_GRID_ID898 -1.4076147 0.0584871 -24.067 < 2e-16 ***
DESTIN_GRID_ID908 -0.0733363 0.0570412 -1.286 0.198558
DESTIN_GRID_ID909 -0.9731296 0.0563495 -17.270 < 2e-16 ***
DESTIN_GRID_ID910 -1.9146930 0.0571989 -33.474 < 2e-16 ***
DESTIN_GRID_ID911 0.1617294 0.0561278 2.881 0.003959 **
DESTIN_GRID_ID912 -1.6566725 0.0565498 -29.296 < 2e-16 ***
DESTIN_GRID_ID915 -1.4988266 0.0563125 -26.616 < 2e-16 ***
DESTIN_GRID_ID917 0.0406137 0.0562610 0.722 0.470369
DESTIN_GRID_ID918 -4.1835040 0.0688968 -60.721 < 2e-16 ***
DESTIN_GRID_ID919 -2.4782804 0.0583805 -42.450 < 2e-16 ***
DESTIN_GRID_ID928 -2.0975536 0.0591366 -35.470 < 2e-16 ***
DESTIN_GRID_ID929 -1.2122534 0.0564966 -21.457 < 2e-16 ***
DESTIN_GRID_ID930 0.0513081 0.0560980 0.915 0.360393
DESTIN_GRID_ID931 -1.4542596 0.0569936 -25.516 < 2e-16 ***
DESTIN_GRID_ID932 -3.1603291 0.0614002 -51.471 < 2e-16 ***
DESTIN_GRID_ID933 -1.1724728 0.0565780 -20.723 < 2e-16 ***
DESTIN_GRID_ID934 -1.3773554 0.0565131 -24.372 < 2e-16 ***
DESTIN_GRID_ID935 0.4598061 0.0560347 8.206 2.29e-16 ***
DESTIN_GRID_ID938 -5.2919818 0.1535327 -34.468 < 2e-16 ***
DESTIN_GRID_ID939 -0.4353142 0.0563720 -7.722 1.14e-14 ***
DESTIN_GRID_ID940 -3.0911103 0.0597857 -51.703 < 2e-16 ***
DESTIN_GRID_ID949 -1.7260292 0.0581089 -29.703 < 2e-16 ***
DESTIN_GRID_ID950 0.2503009 0.0562152 4.453 8.49e-06 ***
DESTIN_GRID_ID951 0.9732599 0.0560377 17.368 < 2e-16 ***
DESTIN_GRID_ID952 -0.5064026 0.0565268 -8.959 < 2e-16 ***
DESTIN_GRID_ID953 -1.0393527 0.0567060 -18.329 < 2e-16 ***
DESTIN_GRID_ID954 -2.9623060 0.0587717 -50.404 < 2e-16 ***
DESTIN_GRID_ID955 -0.1989219 0.0561618 -3.542 0.000397 ***
DESTIN_GRID_ID956 -2.1565616 0.0568036 -37.965 < 2e-16 ***
DESTIN_GRID_ID957 -2.1308841 0.0568193 -37.503 < 2e-16 ***
DESTIN_GRID_ID959 -1.5211525 0.0594156 -25.602 < 2e-16 ***
DESTIN_GRID_ID961 -1.9378276 0.0573969 -33.762 < 2e-16 ***
DESTIN_GRID_ID962 0.1532034 0.0563384 2.719 0.006541 **
DESTIN_GRID_ID970 -0.8120774 0.0565563 -14.359 < 2e-16 ***
DESTIN_GRID_ID971 -0.3468879 0.0561686 -6.176 6.58e-10 ***
DESTIN_GRID_ID972 -1.2165823 0.0565044 -21.531 < 2e-16 ***
DESTIN_GRID_ID974 -1.6157812 0.0571210 -28.287 < 2e-16 ***
DESTIN_GRID_ID975 -2.8543011 0.0587337 -48.597 < 2e-16 ***
DESTIN_GRID_ID976 -2.1164260 0.0570367 -37.106 < 2e-16 ***
DESTIN_GRID_ID977 -1.7839696 0.0564088 -31.626 < 2e-16 ***
DESTIN_GRID_ID978 -2.1807962 0.0572025 -38.124 < 2e-16 ***
DESTIN_GRID_ID982 -2.4553226 0.0571962 -42.928 < 2e-16 ***
DESTIN_GRID_ID983 0.3923990 0.0563858 6.959 3.42e-12 ***
DESTIN_GRID_ID984 1.5975118 0.0564566 28.296 < 2e-16 ***
DESTIN_GRID_ID991 -0.3327533 0.0564562 -5.894 3.77e-09 ***
DESTIN_GRID_ID992 -0.4982260 0.0563626 -8.840 < 2e-16 ***
DESTIN_GRID_ID993 -1.7938759 0.0568611 -31.548 < 2e-16 ***
DESTIN_GRID_ID994 -1.8746299 0.0573389 -32.694 < 2e-16 ***
DESTIN_GRID_ID995 -1.2445682 0.0566533 -21.968 < 2e-16 ***
DESTIN_GRID_ID996 -1.8587548 0.0572827 -32.449 < 2e-16 ***
DESTIN_GRID_ID997 -1.5524976 0.0575529 -26.975 < 2e-16 ***
DESTIN_GRID_ID998 -1.2207416 0.0563536 -21.662 < 2e-16 ***
DESTIN_GRID_ID999 -2.4045463 0.0570854 -42.122 < 2e-16 ***
DESTIN_GRID_ID1001 -1.2718232 0.0581095 -21.887 < 2e-16 ***
DESTIN_GRID_ID1003 0.2513579 0.0561027 4.480 7.45e-06 ***
DESTIN_GRID_ID1004 -0.9789895 0.0562971 -17.390 < 2e-16 ***
DESTIN_GRID_ID1011 -0.7718502 0.0573244 -13.465 < 2e-16 ***
DESTIN_GRID_ID1012 0.1742400 0.0565287 3.082 0.002054 **
DESTIN_GRID_ID1013 -0.4993677 0.0564252 -8.850 < 2e-16 ***
DESTIN_GRID_ID1014 -2.5181528 0.0588502 -42.789 < 2e-16 ***
DESTIN_GRID_ID1015 -0.0638786 0.0562172 -1.136 0.255838
DESTIN_GRID_ID1016 0.2724468 0.0561188 4.855 1.20e-06 ***
DESTIN_GRID_ID1018 -2.1026971 0.0574296 -36.613 < 2e-16 ***
DESTIN_GRID_ID1019 -1.3197447 0.0563783 -23.409 < 2e-16 ***
DESTIN_GRID_ID1023 -2.1569788 0.0577362 -37.359 < 2e-16 ***
DESTIN_GRID_ID1024 -0.9793391 0.0563670 -17.374 < 2e-16 ***
DESTIN_GRID_ID1025 -5.7552764 0.1173907 -49.027 < 2e-16 ***
DESTIN_GRID_ID1033 0.0204920 0.0563443 0.364 0.716088
DESTIN_GRID_ID1034 0.2513431 0.0561835 4.474 7.69e-06 ***
DESTIN_GRID_ID1035 0.1159257 0.0562039 2.063 0.039151 *
DESTIN_GRID_ID1036 0.2628201 0.0561608 4.680 2.87e-06 ***
DESTIN_GRID_ID1037 -0.9052083 0.0563911 -16.052 < 2e-16 ***
DESTIN_GRID_ID1043 -0.5618215 0.0570936 -9.840 < 2e-16 ***
DESTIN_GRID_ID1045 -1.1692434 0.0563385 -20.754 < 2e-16 ***
DESTIN_GRID_ID1046 -0.7591332 0.0563404 -13.474 < 2e-16 ***
DESTIN_GRID_ID1053 0.6075032 0.0562038 10.809 < 2e-16 ***
DESTIN_GRID_ID1054 0.1815205 0.0562366 3.228 0.001247 **
DESTIN_GRID_ID1055 -1.1266867 0.0567490 -19.854 < 2e-16 ***
DESTIN_GRID_ID1056 -1.4875489 0.0572084 -26.002 < 2e-16 ***
DESTIN_GRID_ID1064 -3.7174405 0.1038032 -35.812 < 2e-16 ***
DESTIN_GRID_ID1066 -0.3526665 0.0561629 -6.279 3.40e-10 ***
DESTIN_GRID_ID1067 -5.9092467 0.1534580 -38.507 < 2e-16 ***
DESTIN_GRID_ID1074 -1.5426084 0.0579811 -26.605 < 2e-16 ***
DESTIN_GRID_ID1075 -0.0984324 0.0564286 -1.744 0.081094 .
DESTIN_GRID_ID1076 -0.6570460 0.0564555 -11.638 < 2e-16 ***
DESTIN_GRID_ID1077 -1.3666650 0.0569766 -23.986 < 2e-16 ***
DESTIN_GRID_ID1079 -0.3724194 0.0563186 -6.613 3.77e-11 ***
DESTIN_GRID_ID1085 -1.9697915 0.0738698 -26.666 < 2e-16 ***
DESTIN_GRID_ID1087 -1.1664262 0.0563724 -20.691 < 2e-16 ***
DESTIN_GRID_ID1088 -0.8430664 0.0563055 -14.973 < 2e-16 ***
DESTIN_GRID_ID1094 -3.1207059 0.0791509 -39.427 < 2e-16 ***
DESTIN_GRID_ID1095 -0.7387424 0.0581847 -12.697 < 2e-16 ***
DESTIN_GRID_ID1096 -0.3384658 0.0584011 -5.796 6.81e-09 ***
DESTIN_GRID_ID1097 0.3316250 0.0561504 5.906 3.50e-09 ***
DESTIN_GRID_ID1098 -2.4022207 0.0607937 -39.514 < 2e-16 ***
DESTIN_GRID_ID1099 -1.0859915 0.0566325 -19.176 < 2e-16 ***
DESTIN_GRID_ID1105 0.8509969 0.0567691 14.990 < 2e-16 ***
DESTIN_GRID_ID1106 -4.3006517 0.1102125 -39.021 < 2e-16 ***
DESTIN_GRID_ID1107 -0.8058798 0.0565400 -14.253 < 2e-16 ***
DESTIN_GRID_ID1108 1.1406987 0.0560502 20.351 < 2e-16 ***
DESTIN_GRID_ID1109 -3.5591406 0.0661156 -53.832 < 2e-16 ***
DESTIN_GRID_ID1116 -0.4926957 0.0566718 -8.694 < 2e-16 ***
DESTIN_GRID_ID1117 -0.1987146 0.0565684 -3.513 0.000443 ***
DESTIN_GRID_ID1118 -2.2036468 0.0594704 -37.054 < 2e-16 ***
DESTIN_GRID_ID1119 -1.5058145 0.0571755 -26.337 < 2e-16 ***
DESTIN_GRID_ID1120 -2.0602289 0.0591035 -34.858 < 2e-16 ***
DESTIN_GRID_ID1129 -1.8213306 0.0566334 -32.160 < 2e-16 ***
DESTIN_GRID_ID1130 -1.0127386 0.0562938 -17.990 < 2e-16 ***
DESTIN_GRID_ID1131 0.2364142 0.0564020 4.192 2.77e-05 ***
DESTIN_GRID_ID1136 0.6135175 0.0562267 10.912 < 2e-16 ***
DESTIN_GRID_ID1138 -1.8370626 0.0593287 -30.964 < 2e-16 ***
DESTIN_GRID_ID1139 -1.0152408 0.0565400 -17.956 < 2e-16 ***
DESTIN_GRID_ID1141 -0.9714291 0.0566146 -17.159 < 2e-16 ***
DESTIN_GRID_ID1148 -2.1245919 0.0636417 -33.384 < 2e-16 ***
DESTIN_GRID_ID1149 -2.1896615 0.0577803 -37.896 < 2e-16 ***
DESTIN_GRID_ID1150 -1.8259734 0.0564793 -32.330 < 2e-16 ***
DESTIN_GRID_ID1151 -1.0205637 0.0564109 -18.092 < 2e-16 ***
DESTIN_GRID_ID1158 -1.4049011 0.0572974 -24.519 < 2e-16 ***
DESTIN_GRID_ID1159 -1.2712418 0.0568709 -22.353 < 2e-16 ***
DESTIN_GRID_ID1160 0.3375576 0.0561499 6.012 1.84e-09 ***
DESTIN_GRID_ID1171 -0.8145828 0.0563496 -14.456 < 2e-16 ***
DESTIN_GRID_ID1172 0.4993247 0.0560911 8.902 < 2e-16 ***
DESTIN_GRID_ID1173 0.1210385 0.0562490 2.152 0.031410 *
DESTIN_GRID_ID1174 -2.1484022 0.0692641 -31.018 < 2e-16 ***
DESTIN_GRID_ID1178 0.7957984 0.0561206 14.180 < 2e-16 ***
DESTIN_GRID_ID1179 -0.1599075 0.0562652 -2.842 0.004483 **
DESTIN_GRID_ID1180 -0.0467405 0.0562087 -0.832 0.405662
DESTIN_GRID_ID1181 -1.2939279 0.0567794 -22.789 < 2e-16 ***
DESTIN_GRID_ID1183 0.4618542 0.0561474 8.226 < 2e-16 ***
DESTIN_GRID_ID1190 -1.9339897 0.0617660 -31.312 < 2e-16 ***
DESTIN_GRID_ID1192 -0.8603358 0.0562864 -15.285 < 2e-16 ***
DESTIN_GRID_ID1193 -0.5997636 0.0562687 -10.659 < 2e-16 ***
DESTIN_GRID_ID1194 0.0894112 0.0563283 1.587 0.112440
DESTIN_GRID_ID1200 -0.5136854 0.0565613 -9.082 < 2e-16 ***
DESTIN_GRID_ID1201 -0.7885746 0.0565848 -13.936 < 2e-16 ***
DESTIN_GRID_ID1203 -0.8704054 0.0566653 -15.360 < 2e-16 ***
DESTIN_GRID_ID1204 -1.0031036 0.0567250 -17.684 < 2e-16 ***
DESTIN_GRID_ID1211 -5.9411656 0.4507523 -13.181 < 2e-16 ***
DESTIN_GRID_ID1214 -1.8043700 0.0567549 -31.792 < 2e-16 ***
DESTIN_GRID_ID1215 -0.9426852 0.0572520 -16.466 < 2e-16 ***
DESTIN_GRID_ID1216 -0.3909255 0.0569020 -6.870 6.41e-12 ***
DESTIN_GRID_ID1220 -0.3107502 0.0563734 -5.512 3.54e-08 ***
DESTIN_GRID_ID1221 0.2705195 0.0561641 4.817 1.46e-06 ***
DESTIN_GRID_ID1222 -0.9301858 0.0575808 -16.154 < 2e-16 ***
DESTIN_GRID_ID1223 -1.5909617 0.0575686 -27.636 < 2e-16 ***
DESTIN_GRID_ID1224 -0.7846624 0.0565775 -13.869 < 2e-16 ***
DESTIN_GRID_ID1231 -3.4176319 0.0847200 -40.340 < 2e-16 ***
DESTIN_GRID_ID1232 -1.4182151 0.0601362 -23.583 < 2e-16 ***
DESTIN_GRID_ID1235 -0.8999508 0.0563299 -15.976 < 2e-16 ***
DESTIN_GRID_ID1236 -0.9719200 0.0566558 -17.155 < 2e-16 ***
DESTIN_GRID_ID1241 -1.6038054 0.0574199 -27.931 < 2e-16 ***
DESTIN_GRID_ID1242 -1.1304498 0.0568409 -19.888 < 2e-16 ***
DESTIN_GRID_ID1243 0.0571952 0.0562333 1.017 0.309103
DESTIN_GRID_ID1246 -1.2534208 0.0568249 -22.058 < 2e-16 ***
DESTIN_GRID_ID1256 -1.6537209 0.0567114 -29.160 < 2e-16 ***
DESTIN_GRID_ID1257 -0.4754750 0.0563687 -8.435 < 2e-16 ***
DESTIN_GRID_ID1258 0.5472622 0.0562465 9.730 < 2e-16 ***
DESTIN_GRID_ID1262 -1.9033397 0.0579238 -32.859 < 2e-16 ***
DESTIN_GRID_ID1263 0.4456036 0.0561055 7.942 1.99e-15 ***
DESTIN_GRID_ID1264 -0.3506568 0.0565244 -6.204 5.52e-10 ***
DESTIN_GRID_ID1265 -0.4437133 0.0566178 -7.837 4.61e-15 ***
DESTIN_GRID_ID1266 -0.3975920 0.0564480 -7.044 1.87e-12 ***
DESTIN_GRID_ID1267 -2.0514507 0.0593763 -34.550 < 2e-16 ***
DESTIN_GRID_ID1272 -5.6509125 0.1312585 -43.052 < 2e-16 ***
DESTIN_GRID_ID1273 -0.5107670 0.0564758 -9.044 < 2e-16 ***
DESTIN_GRID_ID1277 -0.3645366 0.0562001 -6.486 8.79e-11 ***
DESTIN_GRID_ID1278 -0.6482251 0.0563585 -11.502 < 2e-16 ***
DESTIN_GRID_ID1283 0.8741669 0.0561059 15.581 < 2e-16 ***
DESTIN_GRID_ID1284 0.4329932 0.0561472 7.712 1.24e-14 ***
DESTIN_GRID_ID1285 0.1815301 0.0562032 3.230 0.001238 **
DESTIN_GRID_ID1286 -0.6983655 0.0569406 -12.265 < 2e-16 ***
DESTIN_GRID_ID1289 -3.1053086 0.0690452 -44.975 < 2e-16 ***
DESTIN_GRID_ID1293 -4.7112912 0.1038025 -45.387 < 2e-16 ***
DESTIN_GRID_ID1294 -0.6664717 0.0567616 -11.742 < 2e-16 ***
DESTIN_GRID_ID1295 -3.1658802 0.0616811 -51.327 < 2e-16 ***
DESTIN_GRID_ID1298 -1.2467705 0.0564802 -22.074 < 2e-16 ***
DESTIN_GRID_ID1299 -1.4291809 0.0568024 -25.161 < 2e-16 ***
DESTIN_GRID_ID1304 -0.0749484 0.0563277 -1.331 0.183328
DESTIN_GRID_ID1305 -0.0684594 0.0561856 -1.218 0.223053
DESTIN_GRID_ID1307 -1.3082803 0.0592465 -22.082 < 2e-16 ***
DESTIN_GRID_ID1308 -0.1559166 0.0562909 -2.770 0.005608 **
DESTIN_GRID_ID1310 -5.0616968 0.2305193 -21.958 < 2e-16 ***
DESTIN_GRID_ID1316 -2.4397547 0.0582385 -41.892 < 2e-16 ***
DESTIN_GRID_ID1317 -2.6939421 0.0578452 -46.572 < 2e-16 ***
DESTIN_GRID_ID1318 -2.7677771 0.0585907 -47.239 < 2e-16 ***
DESTIN_GRID_ID1319 0.1346556 0.0561344 2.399 0.016449 *
DESTIN_GRID_ID1320 -1.7921810 0.0575446 -31.144 < 2e-16 ***
DESTIN_GRID_ID1324 -0.2590469 0.0594490 -4.357 1.32e-05 ***
DESTIN_GRID_ID1325 -2.1771715 0.0584371 -37.257 < 2e-16 ***
DESTIN_GRID_ID1326 -0.5081240 0.0563606 -9.016 < 2e-16 ***
DESTIN_GRID_ID1327 -0.2343029 0.0562791 -4.163 3.14e-05 ***
DESTIN_GRID_ID1328 -0.4299225 0.0564431 -7.617 2.60e-14 ***
DESTIN_GRID_ID1329 -0.6371654 0.0568450 -11.209 < 2e-16 ***
DESTIN_GRID_ID1330 0.7078960 0.0562339 12.588 < 2e-16 ***
DESTIN_GRID_ID1331 -5.8996221 0.2940572 -20.063 < 2e-16 ***
DESTIN_GRID_ID1333 -1.9575651 0.0585166 -33.453 < 2e-16 ***
DESTIN_GRID_ID1334 -1.6219117 0.0577817 -28.070 < 2e-16 ***
DESTIN_GRID_ID1335 0.0661916 0.0562972 1.176 0.239694
DESTIN_GRID_ID1336 -3.2326834 0.0739636 -43.706 < 2e-16 ***
DESTIN_GRID_ID1337 -3.5923955 0.0658534 -54.551 < 2e-16 ***
DESTIN_GRID_ID1338 -3.9010105 0.0630012 -61.920 < 2e-16 ***
DESTIN_GRID_ID1339 -0.2949809 0.0561604 -5.252 1.50e-07 ***
DESTIN_GRID_ID1340 -1.6688436 0.0569377 -29.310 < 2e-16 ***
DESTIN_GRID_ID1341 -5.3577738 0.1106210 -48.434 < 2e-16 ***
DESTIN_GRID_ID1346 -0.3774241 0.0565701 -6.672 2.53e-11 ***
DESTIN_GRID_ID1347 0.8221109 0.0561298 14.647 < 2e-16 ***
DESTIN_GRID_ID1348 -0.6442331 0.0564832 -11.406 < 2e-16 ***
DESTIN_GRID_ID1349 0.3583489 0.0562806 6.367 1.93e-10 ***
DESTIN_GRID_ID1350 -1.2814012 0.0577496 -22.189 < 2e-16 ***
DESTIN_GRID_ID1353 -0.6657291 0.0564848 -11.786 < 2e-16 ***
DESTIN_GRID_ID1354 -1.3430646 0.0569359 -23.589 < 2e-16 ***
DESTIN_GRID_ID1355 -1.7376851 0.0572761 -30.339 < 2e-16 ***
DESTIN_GRID_ID1357 -2.2452227 0.0593065 -37.858 < 2e-16 ***
DESTIN_GRID_ID1358 -0.1456115 0.0561427 -2.594 0.009498 **
DESTIN_GRID_ID1359 -1.4712587 0.0563803 -26.095 < 2e-16 ***
DESTIN_GRID_ID1360 -1.6147466 0.0564757 -28.592 < 2e-16 ***
DESTIN_GRID_ID1361 -1.6236021 0.0569368 -28.516 < 2e-16 ***
DESTIN_GRID_ID1362 -2.7893191 0.0627587 -44.445 < 2e-16 ***
DESTIN_GRID_ID1368 -1.3156453 0.0569374 -23.107 < 2e-16 ***
DESTIN_GRID_ID1369 -1.1202038 0.0567606 -19.736 < 2e-16 ***
DESTIN_GRID_ID1370 0.4618029 0.0561265 8.228 < 2e-16 ***
DESTIN_GRID_ID1371 -0.3756126 0.0564937 -6.649 2.96e-11 ***
DESTIN_GRID_ID1372 -0.3848015 0.0564162 -6.821 9.06e-12 ***
DESTIN_GRID_ID1373 -3.3825092 0.0665030 -50.862 < 2e-16 ***
DESTIN_GRID_ID1374 -2.1833201 0.0581928 -37.519 < 2e-16 ***
DESTIN_GRID_ID1375 -0.3565812 0.0565518 -6.305 2.87e-10 ***
DESTIN_GRID_ID1376 -1.9910206 0.0585657 -33.996 < 2e-16 ***
DESTIN_GRID_ID1379 -5.3854892 0.0957315 -56.256 < 2e-16 ***
DESTIN_GRID_ID1380 0.3878718 0.0560726 6.917 4.60e-12 ***
DESTIN_GRID_ID1381 0.5873184 0.0560611 10.476 < 2e-16 ***
DESTIN_GRID_ID1382 -0.2054129 0.0562145 -3.654 0.000258 ***
DESTIN_GRID_ID1383 -2.9021304 0.0594870 -48.786 < 2e-16 ***
DESTIN_GRID_ID1388 -0.5451870 0.0564540 -9.657 < 2e-16 ***
DESTIN_GRID_ID1389 -0.7873025 0.0565796 -13.915 < 2e-16 ***
DESTIN_GRID_ID1390 -0.4417250 0.0564747 -7.822 5.21e-15 ***
DESTIN_GRID_ID1391 0.2765642 0.0562222 4.919 8.69e-07 ***
DESTIN_GRID_ID1392 -0.2444473 0.0571794 -4.275 1.91e-05 ***
DESTIN_GRID_ID1393 -0.9615063 0.0566335 -16.978 < 2e-16 ***
DESTIN_GRID_ID1394 -0.6384301 0.0563636 -11.327 < 2e-16 ***
DESTIN_GRID_ID1395 -1.1053054 0.0565310 -19.552 < 2e-16 ***
DESTIN_GRID_ID1396 -0.3589208 0.0562611 -6.380 1.78e-10 ***
DESTIN_GRID_ID1397 -1.4677042 0.0566852 -25.892 < 2e-16 ***
DESTIN_GRID_ID1398 -1.6592032 0.0578736 -28.669 < 2e-16 ***
DESTIN_GRID_ID1400 -2.2282641 0.0571073 -39.019 < 2e-16 ***
DESTIN_GRID_ID1401 0.1294066 0.0560726 2.308 0.021008 *
DESTIN_GRID_ID1402 -1.1912604 0.0562854 -21.165 < 2e-16 ***
DESTIN_GRID_ID1404 -1.9088433 0.0619295 -30.823 < 2e-16 ***
DESTIN_GRID_ID1410 0.0070657 0.0562372 0.126 0.900016
DESTIN_GRID_ID1411 -0.4132232 0.0565573 -7.306 2.75e-13 ***
DESTIN_GRID_ID1412 0.1398474 0.0561793 2.489 0.012799 *
DESTIN_GRID_ID1413 -0.5149771 0.0564083 -9.129 < 2e-16 ***
DESTIN_GRID_ID1414 -0.5749905 0.0563248 -10.208 < 2e-16 ***
DESTIN_GRID_ID1415 -0.2921167 0.0562753 -5.191 2.09e-07 ***
DESTIN_GRID_ID1416 -0.8247100 0.0564683 -14.605 < 2e-16 ***
DESTIN_GRID_ID1417 -0.6522440 0.0562679 -11.592 < 2e-16 ***
DESTIN_GRID_ID1418 -0.7618937 0.0563158 -13.529 < 2e-16 ***
DESTIN_GRID_ID1419 -1.0872882 0.0565368 -19.232 < 2e-16 ***
DESTIN_GRID_ID1422 -1.5216896 0.0563314 -27.013 < 2e-16 ***
DESTIN_GRID_ID1423 -1.0802624 0.0562571 -19.202 < 2e-16 ***
DESTIN_GRID_ID1430 0.2341785 0.0562482 4.163 3.14e-05 ***
DESTIN_GRID_ID1431 0.5077023 0.0561420 9.043 < 2e-16 ***
DESTIN_GRID_ID1432 0.2190216 0.0561560 3.900 9.61e-05 ***
DESTIN_GRID_ID1433 -0.6430583 0.0568916 -11.303 < 2e-16 ***
DESTIN_GRID_ID1434 0.3339650 0.0561564 5.947 2.73e-09 ***
DESTIN_GRID_ID1435 -0.2120603 0.0562003 -3.773 0.000161 ***
DESTIN_GRID_ID1436 -1.5270701 0.0570607 -26.762 < 2e-16 ***
DESTIN_GRID_ID1437 -0.9122757 0.0563979 -16.176 < 2e-16 ***
DESTIN_GRID_ID1438 -0.4104049 0.0561692 -7.307 2.74e-13 ***
DESTIN_GRID_ID1439 0.4025573 0.0561057 7.175 7.23e-13 ***
DESTIN_GRID_ID1440 -0.3741862 0.0564149 -6.633 3.29e-11 ***
DESTIN_GRID_ID1442 -3.4577927 0.0590847 -58.523 < 2e-16 ***
DESTIN_GRID_ID1443 -1.5025943 0.0563259 -26.677 < 2e-16 ***
DESTIN_GRID_ID1444 -0.2869472 0.0562932 -5.097 3.44e-07 ***
DESTIN_GRID_ID1452 0.9306557 0.0560831 16.594 < 2e-16 ***
DESTIN_GRID_ID1453 -0.0443476 0.0562816 -0.788 0.430721
DESTIN_GRID_ID1454 -1.0567194 0.0574848 -18.383 < 2e-16 ***
DESTIN_GRID_ID1455 -0.4243451 0.0564861 -7.512 5.81e-14 ***
DESTIN_GRID_ID1456 -0.4689799 0.0563360 -8.325 < 2e-16 ***
DESTIN_GRID_ID1457 0.0770079 0.0562060 1.370 0.170655
DESTIN_GRID_ID1458 1.0038970 0.0560513 17.910 < 2e-16 ***
DESTIN_GRID_ID1459 -1.7799877 0.0567253 -31.379 < 2e-16 ***
DESTIN_GRID_ID1460 -0.5821813 0.0561938 -10.360 < 2e-16 ***
DESTIN_GRID_ID1461 -0.6696925 0.0564384 -11.866 < 2e-16 ***
DESTIN_GRID_ID1464 -1.5098781 0.0564302 -26.757 < 2e-16 ***
DESTIN_GRID_ID1465 -2.3828620 0.0570496 -41.768 < 2e-16 ***
DESTIN_GRID_ID1472 -0.1417830 0.0565339 -2.508 0.012144 *
DESTIN_GRID_ID1473 0.7301623 0.0561207 13.011 < 2e-16 ***
DESTIN_GRID_ID1474 0.4363012 0.0561078 7.776 7.48e-15 ***
DESTIN_GRID_ID1475 0.0112977 0.0561990 0.201 0.840674
DESTIN_GRID_ID1476 -0.8367445 0.0565217 -14.804 < 2e-16 ***
DESTIN_GRID_ID1477 0.8919219 0.0560439 15.915 < 2e-16 ***
DESTIN_GRID_ID1478 -0.6865055 0.0562569 -12.203 < 2e-16 ***
DESTIN_GRID_ID1479 -1.4541570 0.0565120 -25.732 < 2e-16 ***
DESTIN_GRID_ID1480 0.7522278 0.0560506 13.421 < 2e-16 ***
DESTIN_GRID_ID1481 -0.9212336 0.0564496 -16.320 < 2e-16 ***
DESTIN_GRID_ID1482 0.3116281 0.0562170 5.543 2.97e-08 ***
DESTIN_GRID_ID1485 -2.4873717 0.0570579 -43.594 < 2e-16 ***
DESTIN_GRID_ID1494 0.5583516 0.0561643 9.941 < 2e-16 ***
DESTIN_GRID_ID1495 -0.4091541 0.0563572 -7.260 3.87e-13 ***
DESTIN_GRID_ID1496 0.4096215 0.0561172 7.299 2.89e-13 ***
DESTIN_GRID_ID1497 -0.9044266 0.0565889 -15.982 < 2e-16 ***
DESTIN_GRID_ID1498 -0.7545776 0.0564189 -13.375 < 2e-16 ***
DESTIN_GRID_ID1499 -0.4867120 0.0561918 -8.662 < 2e-16 ***
DESTIN_GRID_ID1500 -0.7819313 0.0566493 -13.803 < 2e-16 ***
DESTIN_GRID_ID1501 -0.1597557 0.0561350 -2.846 0.004428 **
DESTIN_GRID_ID1502 -0.3195947 0.0561734 -5.689 1.27e-08 ***
DESTIN_GRID_ID1506 -3.1835783 0.0885150 -35.967 < 2e-16 ***
DESTIN_GRID_ID1515 -0.3475809 0.0579431 -5.999 1.99e-09 ***
DESTIN_GRID_ID1516 0.4686079 0.0561148 8.351 < 2e-16 ***
DESTIN_GRID_ID1517 -0.3970991 0.0564547 -7.034 2.01e-12 ***
DESTIN_GRID_ID1518 -1.2368191 0.0566954 -21.815 < 2e-16 ***
DESTIN_GRID_ID1519 -1.0862840 0.0566944 -19.160 < 2e-16 ***
DESTIN_GRID_ID1520 -1.2581816 0.0564633 -22.283 < 2e-16 ***
DESTIN_GRID_ID1521 -1.2072628 0.0564993 -21.368 < 2e-16 ***
DESTIN_GRID_ID1522 -0.6155585 0.0562465 -10.944 < 2e-16 ***
DESTIN_GRID_ID1523 0.7629720 0.0561856 13.580 < 2e-16 ***
DESTIN_GRID_ID1524 -1.6673007 0.0574511 -29.021 < 2e-16 ***
DESTIN_GRID_ID1527 -4.1477081 0.0654104 -63.411 < 2e-16 ***
DESTIN_GRID_ID1535 -0.7995649 0.0907170 -8.814 < 2e-16 ***
DESTIN_GRID_ID1536 -1.8502045 0.0634229 -29.172 < 2e-16 ***
DESTIN_GRID_ID1537 0.0266097 0.0563666 0.472 0.636868
DESTIN_GRID_ID1538 -0.2444498 0.0562783 -4.344 1.40e-05 ***
DESTIN_GRID_ID1539 -0.2701121 0.0562069 -4.806 1.54e-06 ***
DESTIN_GRID_ID1540 -0.9944909 0.0563676 -17.643 < 2e-16 ***
DESTIN_GRID_ID1541 -0.2286825 0.0565693 -4.043 5.29e-05 ***
DESTIN_GRID_ID1542 -0.9871666 0.0567704 -17.389 < 2e-16 ***
DESTIN_GRID_ID1543 -1.4454525 0.0631163 -22.901 < 2e-16 ***
DESTIN_GRID_ID1544 -1.2339003 0.0568346 -21.710 < 2e-16 ***
DESTIN_GRID_ID1547 -1.8297492 0.0577965 -31.658 < 2e-16 ***
DESTIN_GRID_ID1556 -0.8215764 0.0924554 -8.886 < 2e-16 ***
DESTIN_GRID_ID1557 -1.4817580 0.0599488 -24.717 < 2e-16 ***
DESTIN_GRID_ID1558 -0.3721279 0.0576834 -6.451 1.11e-10 ***
DESTIN_GRID_ID1559 0.2679318 0.0561387 4.773 1.82e-06 ***
DESTIN_GRID_ID1560 0.2724083 0.0561237 4.854 1.21e-06 ***
DESTIN_GRID_ID1561 -0.6314256 0.0564407 -11.187 < 2e-16 ***
DESTIN_GRID_ID1562 -2.5774826 0.0584790 -44.075 < 2e-16 ***
DESTIN_GRID_ID1563 -1.7704476 0.0568604 -31.137 < 2e-16 ***
DESTIN_GRID_ID1564 -1.3743092 0.0566408 -24.264 < 2e-16 ***
DESTIN_GRID_ID1565 -0.7835988 0.0563599 -13.903 < 2e-16 ***
DESTIN_GRID_ID1566 -2.5631257 0.0585157 -43.802 < 2e-16 ***
DESTIN_GRID_ID1567 -2.3793086 0.0587016 -40.532 < 2e-16 ***
DESTIN_GRID_ID1568 -1.3354385 0.0570625 -23.403 < 2e-16 ***
DESTIN_GRID_ID1578 -1.3244657 0.1247767 -10.615 < 2e-16 ***
DESTIN_GRID_ID1580 -2.6161969 0.0633105 -41.323 < 2e-16 ***
DESTIN_GRID_ID1581 -0.1908107 0.0562212 -3.394 0.000689 ***
DESTIN_GRID_ID1582 0.0361902 0.0561306 0.645 0.519090
DESTIN_GRID_ID1583 -1.9324753 0.0602860 -32.055 < 2e-16 ***
DESTIN_GRID_ID1584 -1.6504462 0.0574282 -28.739 < 2e-16 ***
DESTIN_GRID_ID1585 -1.3197221 0.0567274 -23.264 < 2e-16 ***
DESTIN_GRID_ID1586 -0.5048567 0.0562617 -8.973 < 2e-16 ***
DESTIN_GRID_ID1589 -2.7744482 0.0601086 -46.157 < 2e-16 ***
DESTIN_GRID_ID1590 -1.5780260 0.0575747 -27.408 < 2e-16 ***
DESTIN_GRID_ID1600 -0.7563546 0.0583710 -12.958 < 2e-16 ***
DESTIN_GRID_ID1601 -1.1240272 0.0565219 -19.887 < 2e-16 ***
DESTIN_GRID_ID1602 -0.7855477 0.0564624 -13.913 < 2e-16 ***
DESTIN_GRID_ID1603 0.3392110 0.0561366 6.043 1.52e-09 ***
DESTIN_GRID_ID1604 -1.9435393 0.0571297 -34.020 < 2e-16 ***
DESTIN_GRID_ID1605 -0.9038678 0.0563199 -16.049 < 2e-16 ***
DESTIN_GRID_ID1606 -1.7454120 0.0580662 -30.059 < 2e-16 ***
DESTIN_GRID_ID1607 -0.3232986 0.0561599 -5.757 8.57e-09 ***
DESTIN_GRID_ID1608 -1.1749869 0.0564075 -20.830 < 2e-16 ***
DESTIN_GRID_ID1609 -0.4081415 0.0562388 -7.257 3.95e-13 ***
DESTIN_GRID_ID1610 -2.5454704 0.0625812 -40.675 < 2e-16 ***
DESTIN_GRID_ID1622 -0.5083743 0.0574504 -8.849 < 2e-16 ***
DESTIN_GRID_ID1623 -0.0818152 0.0561608 -1.457 0.145171
DESTIN_GRID_ID1624 0.4796137 0.0561277 8.545 < 2e-16 ***
DESTIN_GRID_ID1625 -0.4424004 0.0563039 -7.857 3.92e-15 ***
DESTIN_GRID_ID1626 1.2279048 0.0560350 21.913 < 2e-16 ***
DESTIN_GRID_ID1627 -1.8684061 0.0567619 -32.917 < 2e-16 ***
DESTIN_GRID_ID1628 0.1602513 0.0561125 2.856 0.004292 **
DESTIN_GRID_ID1629 -2.9023448 0.0582079 -49.862 < 2e-16 ***
DESTIN_GRID_ID1630 -2.4325347 0.0572680 -42.476 < 2e-16 ***
DESTIN_GRID_ID1631 -2.6869338 0.0587587 -45.728 < 2e-16 ***
DESTIN_GRID_ID1642 -2.8234818 0.0654092 -43.166 < 2e-16 ***
DESTIN_GRID_ID1643 -0.5708194 0.0563256 -10.134 < 2e-16 ***
DESTIN_GRID_ID1644 -0.5606081 0.0565917 -9.906 < 2e-16 ***
DESTIN_GRID_ID1645 -0.7352777 0.0563904 -13.039 < 2e-16 ***
DESTIN_GRID_ID1646 -0.4442121 0.0565832 -7.851 4.14e-15 ***
DESTIN_GRID_ID1647 -1.2236338 0.0563741 -21.706 < 2e-16 ***
DESTIN_GRID_ID1648 -1.0839224 0.0562970 -19.254 < 2e-16 ***
DESTIN_GRID_ID1649 -0.5381008 0.0561567 -9.582 < 2e-16 ***
DESTIN_GRID_ID1650 -1.4967568 0.0565556 -26.465 < 2e-16 ***
DESTIN_GRID_ID1664 -5.0300885 0.1428153 -35.221 < 2e-16 ***
DESTIN_GRID_ID1665 0.0306507 0.0561473 0.546 0.585137
DESTIN_GRID_ID1666 0.0730552 0.0561414 1.301 0.193166
DESTIN_GRID_ID1667 -0.6382262 0.0578885 -11.025 < 2e-16 ***
DESTIN_GRID_ID1668 -1.2075839 0.0564628 -21.387 < 2e-16 ***
DESTIN_GRID_ID1670 -0.7123790 0.0561804 -12.680 < 2e-16 ***
DESTIN_GRID_ID1671 -1.2911898 0.0573069 -22.531 < 2e-16 ***
DESTIN_GRID_ID1672 -2.2244148 0.0574209 -38.739 < 2e-16 ***
DESTIN_GRID_ID1684 -0.2375400 0.0567495 -4.186 2.84e-05 ***
DESTIN_GRID_ID1685 -1.4775285 0.0568455 -25.992 < 2e-16 ***
DESTIN_GRID_ID1686 -0.5878988 0.0563001 -10.442 < 2e-16 ***
DESTIN_GRID_ID1687 -0.3304564 0.0564310 -5.856 4.74e-09 ***
DESTIN_GRID_ID1688 -1.1394150 0.0564618 -20.180 < 2e-16 ***
DESTIN_GRID_ID1689 -1.8984741 0.0569710 -33.324 < 2e-16 ***
DESTIN_GRID_ID1690 -2.5897051 0.0577033 -44.880 < 2e-16 ***
DESTIN_GRID_ID1691 -0.6174263 0.0561716 -10.992 < 2e-16 ***
DESTIN_GRID_ID1692 -2.7094923 0.0580714 -46.658 < 2e-16 ***
DESTIN_GRID_ID1706 -0.7059904 0.0565845 -12.477 < 2e-16 ***
DESTIN_GRID_ID1707 -1.5007164 0.0566925 -26.471 < 2e-16 ***
DESTIN_GRID_ID1708 -0.9055526 0.0564033 -16.055 < 2e-16 ***
DESTIN_GRID_ID1709 -0.1496906 0.0561907 -2.664 0.007722 **
DESTIN_GRID_ID1710 -0.3278023 0.0562210 -5.831 5.52e-09 ***
DESTIN_GRID_ID1711 0.1325654 0.0561125 2.362 0.018152 *
DESTIN_GRID_ID1712 -0.7820813 0.0561846 -13.920 < 2e-16 ***
DESTIN_GRID_ID1713 -3.1567412 0.0584361 -54.020 < 2e-16 ***
DESTIN_GRID_ID1714 -1.8325666 0.0567091 -32.315 < 2e-16 ***
DESTIN_GRID_ID1727 -0.2232911 0.0562905 -3.967 7.29e-05 ***
DESTIN_GRID_ID1728 -0.2038589 0.0561890 -3.628 0.000286 ***
DESTIN_GRID_ID1729 -0.0947607 0.0561655 -1.687 0.091571 .
DESTIN_GRID_ID1730 -1.0635538 0.0566158 -18.785 < 2e-16 ***
DESTIN_GRID_ID1731 -0.2555691 0.0561794 -4.549 5.39e-06 ***
DESTIN_GRID_ID1732 -0.9388520 0.0562216 -16.699 < 2e-16 ***
DESTIN_GRID_ID1733 -2.1062001 0.0566964 -37.149 < 2e-16 ***
DESTIN_GRID_ID1734 -0.8955159 0.0562161 -15.930 < 2e-16 ***
DESTIN_GRID_ID1735 -1.7474385 0.0583486 -29.948 < 2e-16 ***
DESTIN_GRID_ID1748 -1.2666544 0.0568279 -22.289 < 2e-16 ***
DESTIN_GRID_ID1749 -0.0709001 0.0561503 -1.263 0.206703
DESTIN_GRID_ID1750 -0.0876593 0.0561620 -1.561 0.118564
DESTIN_GRID_ID1751 -0.5342335 0.0563557 -9.480 < 2e-16 ***
DESTIN_GRID_ID1753 -0.3606659 0.0561781 -6.420 1.36e-10 ***
DESTIN_GRID_ID1754 0.4760227 0.0560548 8.492 < 2e-16 ***
DESTIN_GRID_ID1755 -0.3195111 0.0561098 -5.694 1.24e-08 ***
DESTIN_GRID_ID1756 -1.3663682 0.0563017 -24.269 < 2e-16 ***
DESTIN_GRID_ID1757 -3.6827361 0.0606530 -60.718 < 2e-16 ***
DESTIN_GRID_ID1769 -0.5319071 0.0563424 -9.441 < 2e-16 ***
DESTIN_GRID_ID1770 -0.8001897 0.0566400 -14.128 < 2e-16 ***
DESTIN_GRID_ID1771 -0.0003885 0.0562397 -0.007 0.994488
DESTIN_GRID_ID1772 1.1043463 0.0564600 19.560 < 2e-16 ***
DESTIN_GRID_ID1774 -1.5165638 0.0564622 -26.860 < 2e-16 ***
DESTIN_GRID_ID1775 -1.9375849 0.0565775 -34.247 < 2e-16 ***
DESTIN_GRID_ID1776 0.2500387 0.0560639 4.460 8.20e-06 ***
DESTIN_GRID_ID1777 -1.8927256 0.0565409 -33.475 < 2e-16 ***
DESTIN_GRID_ID1778 -2.8474570 0.0605472 -47.029 < 2e-16 ***
DESTIN_GRID_ID1790 0.0002262 0.0562590 0.004 0.996792
DESTIN_GRID_ID1791 -0.6614622 0.0563974 -11.729 < 2e-16 ***
DESTIN_GRID_ID1792 -0.3735370 0.0564859 -6.613 3.77e-11 ***
DESTIN_GRID_ID1793 -0.3844375 0.0563039 -6.828 8.62e-12 ***
DESTIN_GRID_ID1794 1.4147227 0.0564994 25.040 < 2e-16 ***
DESTIN_GRID_ID1795 -2.8404834 0.0599596 -47.373 < 2e-16 ***
DESTIN_GRID_ID1796 -0.8483657 0.0562570 -15.080 < 2e-16 ***
DESTIN_GRID_ID1797 -1.2735430 0.0562841 -22.627 < 2e-16 ***
DESTIN_GRID_ID1798 -1.1976639 0.0562562 -21.289 < 2e-16 ***
DESTIN_GRID_ID1799 -2.1380035 0.0568003 -37.641 < 2e-16 ***
DESTIN_GRID_ID1800 -4.2612553 0.0860338 -49.530 < 2e-16 ***
DESTIN_GRID_ID1811 -1.0370702 0.0566770 -18.298 < 2e-16 ***
DESTIN_GRID_ID1812 0.3986053 0.0560941 7.106 1.19e-12 ***
DESTIN_GRID_ID1813 0.6332645 0.0560818 11.292 < 2e-16 ***
DESTIN_GRID_ID1817 -2.6851926 0.0577248 -46.517 < 2e-16 ***
DESTIN_GRID_ID1818 -1.5850764 0.0563196 -28.144 < 2e-16 ***
DESTIN_GRID_ID1819 0.0858283 0.0560779 1.531 0.125888
DESTIN_GRID_ID1820 -4.6017352 0.0758046 -60.705 < 2e-16 ***
DESTIN_GRID_ID1832 0.1749103 0.0561919 3.113 0.001854 **
DESTIN_GRID_ID1833 -1.0780352 0.0565051 -19.079 < 2e-16 ***
DESTIN_GRID_ID1834 -1.0606681 0.0564268 -18.797 < 2e-16 ***
DESTIN_GRID_ID1835 -0.9708715 0.0565327 -17.174 < 2e-16 ***
DESTIN_GRID_ID1837 -1.1085426 0.0577574 -19.193 < 2e-16 ***
DESTIN_GRID_ID1839 -2.7475239 0.0576325 -47.673 < 2e-16 ***
DESTIN_GRID_ID1840 0.1509157 0.0560887 2.691 0.007131 **
DESTIN_GRID_ID1841 -3.7467300 0.0627604 -59.699 < 2e-16 ***
DESTIN_GRID_ID1842 -1.2336089 0.0589006 -20.944 < 2e-16 ***
DESTIN_GRID_ID1853 -0.5643922 0.0563101 -10.023 < 2e-16 ***
DESTIN_GRID_ID1854 -0.4014980 0.0562571 -7.137 9.55e-13 ***
DESTIN_GRID_ID1855 -0.0047396 0.0561870 -0.084 0.932775
DESTIN_GRID_ID1858 0.0564477 0.0566229 0.997 0.318810
DESTIN_GRID_ID1860 -2.1089557 0.0602264 -35.017 < 2e-16 ***
DESTIN_GRID_ID1861 -1.3619344 0.0563357 -24.175 < 2e-16 ***
DESTIN_GRID_ID1874 -1.0682737 0.0569907 -18.745 < 2e-16 ***
DESTIN_GRID_ID1875 -2.8397822 0.0608752 -46.649 < 2e-16 ***
DESTIN_GRID_ID1876 -1.5107694 0.0612414 -24.669 < 2e-16 ***
DESTIN_GRID_ID1877 -0.2172391 0.0562244 -3.864 0.000112 ***
DESTIN_GRID_ID1880 -0.8703498 0.0577658 -15.067 < 2e-16 ***
DESTIN_GRID_ID1882 -1.4596389 0.0563900 -25.885 < 2e-16 ***
DESTIN_GRID_ID1883 -2.5834125 0.0600858 -42.995 < 2e-16 ***
DESTIN_GRID_ID1895 -0.1003154 0.0562295 -1.784 0.074418 .
DESTIN_GRID_ID1896 -1.2339552 0.0565801 -21.809 < 2e-16 ***
DESTIN_GRID_ID1897 -2.0654867 0.0575050 -35.918 < 2e-16 ***
DESTIN_GRID_ID1898 -2.4097851 0.0615814 -39.132 < 2e-16 ***
DESTIN_GRID_ID1901 -1.3964685 0.0596212 -23.422 < 2e-16 ***
DESTIN_GRID_ID1903 -3.0174522 0.0592683 -50.912 < 2e-16 ***
DESTIN_GRID_ID1917 -1.4424921 0.0568538 -25.372 < 2e-16 ***
DESTIN_GRID_ID1918 -0.2224026 0.0564156 -3.942 8.07e-05 ***
DESTIN_GRID_ID1919 -0.1003840 0.0562024 -1.786 0.074080 .
DESTIN_GRID_ID1922 -0.1668297 0.0570013 -2.927 0.003425 **
DESTIN_GRID_ID1924 -3.2602061 0.0608916 -53.541 < 2e-16 ***
DESTIN_GRID_ID1937 -0.7554426 0.0565440 -13.360 < 2e-16 ***
DESTIN_GRID_ID1938 -0.0025386 0.0561850 -0.045 0.963961
DESTIN_GRID_ID1939 -1.2851046 0.0567778 -22.634 < 2e-16 ***
DESTIN_GRID_ID1942 -1.5203529 0.0591823 -25.689 < 2e-16 ***
DESTIN_GRID_ID1959 -1.2520703 0.0569317 -21.993 < 2e-16 ***
DESTIN_GRID_ID1960 1.0990867 0.0560435 19.611 < 2e-16 ***
DESTIN_GRID_ID1961 -1.4085173 0.0569147 -24.748 < 2e-16 ***
DESTIN_GRID_ID1962 -0.5941571 0.0563418 -10.546 < 2e-16 ***
DESTIN_GRID_ID1964 0.1174481 0.0571507 2.055 0.039873 *
DESTIN_GRID_ID1979 -0.7233074 0.0566366 -12.771 < 2e-16 ***
DESTIN_GRID_ID1980 -1.0279060 0.0564444 -18.211 < 2e-16 ***
DESTIN_GRID_ID1981 -1.0782036 0.0565007 -19.083 < 2e-16 ***
DESTIN_GRID_ID1982 -0.5886939 0.0565677 -10.407 < 2e-16 ***
DESTIN_GRID_ID1983 -0.7333040 0.0563589 -13.011 < 2e-16 ***
DESTIN_GRID_ID1984 -0.5592396 0.0563427 -9.926 < 2e-16 ***
DESTIN_GRID_ID1985 -0.4367130 0.0563011 -7.757 8.71e-15 ***
DESTIN_GRID_ID2001 -0.7424787 0.0564226 -13.159 < 2e-16 ***
DESTIN_GRID_ID2002 -0.7421737 0.0562690 -13.190 < 2e-16 ***
DESTIN_GRID_ID2003 -0.0817493 0.0561769 -1.455 0.145611
DESTIN_GRID_ID2004 0.0764432 0.0561681 1.361 0.173523
DESTIN_GRID_ID2005 -0.9156454 0.0564091 -16.232 < 2e-16 ***
DESTIN_GRID_ID2006 -0.0057881 0.0562003 -0.103 0.917971
DESTIN_GRID_ID2007 -3.4383673 0.0650368 -52.868 < 2e-16 ***
DESTIN_GRID_ID2022 -0.2260020 0.0564227 -4.006 6.19e-05 ***
DESTIN_GRID_ID2023 -0.2243879 0.0562040 -3.992 6.54e-05 ***
DESTIN_GRID_ID2024 0.1015354 0.0561341 1.809 0.070482 .
DESTIN_GRID_ID2025 -1.3050802 0.0564536 -23.118 < 2e-16 ***
DESTIN_GRID_ID2026 -1.9690633 0.0574411 -34.280 < 2e-16 ***
DESTIN_GRID_ID2027 0.0942057 0.0561699 1.677 0.093512 .
DESTIN_GRID_ID2043 -1.6802640 0.0573761 -29.285 < 2e-16 ***
DESTIN_GRID_ID2044 -0.7269773 0.0563394 -12.904 < 2e-16 ***
DESTIN_GRID_ID2045 -1.3321575 0.0573653 -23.222 < 2e-16 ***
DESTIN_GRID_ID2046 0.0220006 0.0561198 0.392 0.695037
DESTIN_GRID_ID2047 -1.8995960 0.0569317 -33.366 < 2e-16 ***
DESTIN_GRID_ID2048 -1.6083955 0.0567692 -28.332 < 2e-16 ***
DESTIN_GRID_ID2049 -3.3525747 0.0636989 -52.632 < 2e-16 ***
DESTIN_GRID_ID2064 -0.8409802 0.0564957 -14.886 < 2e-16 ***
DESTIN_GRID_ID2065 -0.9683981 0.0564870 -17.144 < 2e-16 ***
DESTIN_GRID_ID2066 -3.3097427 0.0676822 -48.901 < 2e-16 ***
DESTIN_GRID_ID2067 1.5674872 0.0560325 27.975 < 2e-16 ***
DESTIN_GRID_ID2068 -1.9884626 0.0580672 -34.244 < 2e-16 ***
DESTIN_GRID_ID2069 -1.4285035 0.0567739 -25.161 < 2e-16 ***
DESTIN_GRID_ID2085 -0.6493191 0.0565079 -11.491 < 2e-16 ***
DESTIN_GRID_ID2086 0.6636016 0.0561241 11.824 < 2e-16 ***
DESTIN_GRID_ID2087 0.3540287 0.0561415 6.306 2.86e-10 ***
DESTIN_GRID_ID2088 -0.9028251 0.0563186 -16.031 < 2e-16 ***
DESTIN_GRID_ID2089 -1.3768168 0.0567844 -24.246 < 2e-16 ***
DESTIN_GRID_ID2090 1.2618872 0.0560521 22.513 < 2e-16 ***
DESTIN_GRID_ID2091 -4.1298108 0.0905412 -45.613 < 2e-16 ***
DESTIN_GRID_ID2105 -1.5115088 0.0870251 -17.369 < 2e-16 ***
DESTIN_GRID_ID2106 -2.1896308 0.0581561 -37.651 < 2e-16 ***
DESTIN_GRID_ID2107 0.5329657 0.0561260 9.496 < 2e-16 ***
DESTIN_GRID_ID2108 0.1320797 0.0562085 2.350 0.018783 *
DESTIN_GRID_ID2109 -1.3418811 0.0564644 -23.765 < 2e-16 ***
DESTIN_GRID_ID2110 -2.0051222 0.0573871 -34.940 < 2e-16 ***
DESTIN_GRID_ID2111 -3.1711484 0.0667261 -47.525 < 2e-16 ***
DESTIN_GRID_ID2128 -0.4469066 0.0566514 -7.889 3.05e-15 ***
DESTIN_GRID_ID2129 -0.7793076 0.0570877 -13.651 < 2e-16 ***
DESTIN_GRID_ID2130 -0.7417364 0.0562978 -13.175 < 2e-16 ***
DESTIN_GRID_ID2131 -0.7742401 0.0565326 -13.695 < 2e-16 ***
DESTIN_GRID_ID2132 -1.3530148 0.0566295 -23.892 < 2e-16 ***
DESTIN_GRID_ID2148 -1.3812584 0.0584856 -23.617 < 2e-16 ***
DESTIN_GRID_ID2149 -1.3359996 0.0571863 -23.362 < 2e-16 ***
DESTIN_GRID_ID2150 -1.1389131 0.0567840 -20.057 < 2e-16 ***
DESTIN_GRID_ID2151 0.6927875 0.0560811 12.353 < 2e-16 ***
DESTIN_GRID_ID2152 -0.3600313 0.0562715 -6.398 1.57e-10 ***
DESTIN_GRID_ID2153 -1.6445268 0.0573770 -28.662 < 2e-16 ***
DESTIN_GRID_ID2171 -0.1504116 0.0563111 -2.671 0.007561 **
DESTIN_GRID_ID2172 -1.7996115 0.0573137 -31.399 < 2e-16 ***
DESTIN_GRID_ID2173 -1.3456379 0.0565392 -23.800 < 2e-16 ***
DESTIN_GRID_ID2174 -0.6460881 0.0564149 -11.452 < 2e-16 ***
DESTIN_GRID_ID2191 0.0462125 0.0566390 0.816 0.414550
DESTIN_GRID_ID2192 -1.1645794 0.0571751 -20.369 < 2e-16 ***
DESTIN_GRID_ID2193 -0.4725554 0.0563858 -8.381 < 2e-16 ***
DESTIN_GRID_ID2194 -0.5655078 0.0563188 -10.041 < 2e-16 ***
DESTIN_GRID_ID2195 -2.6188590 0.0695562 -37.651 < 2e-16 ***
DESTIN_GRID_ID2212 0.4022417 0.0577883 6.961 3.39e-12 ***
DESTIN_GRID_ID2213 -0.2630728 0.0567461 -4.636 3.55e-06 ***
DESTIN_GRID_ID2214 0.6408292 0.0565127 11.340 < 2e-16 ***
DESTIN_GRID_ID2215 -1.1686576 0.0569498 -20.521 < 2e-16 ***
DESTIN_GRID_ID2216 -0.2237773 0.0563362 -3.972 7.12e-05 ***
DESTIN_GRID_ID2233 0.5528177 0.0569666 9.704 < 2e-16 ***
DESTIN_GRID_ID2234 1.1636997 0.0566599 20.538 < 2e-16 ***
DESTIN_GRID_ID2235 -0.2210756 0.0568078 -3.892 9.96e-05 ***
DESTIN_GRID_ID2236 -1.6725840 0.0577444 -28.965 < 2e-16 ***
DESTIN_GRID_ID2237 -0.1447585 0.0572494 -2.529 0.011453 *
DESTIN_GRID_ID2256 0.0240725 0.0574691 0.419 0.675306
DESTIN_GRID_ID2257 -2.5383261 0.0633018 -40.099 < 2e-16 ***
DESTIN_GRID_ID2258 -0.4025875 0.0564925 -7.126 1.03e-12 ***
DESTIN_GRID_ID2259 0.6390185 0.0570166 11.208 < 2e-16 ***
DESTIN_GRID_ID2277 -1.2058625 0.0620193 -19.443 < 2e-16 ***
DESTIN_GRID_ID2278 -1.0364124 0.0586762 -17.663 < 2e-16 ***
DESTIN_GRID_ID2279 -0.2119838 0.0565156 -3.751 0.000176 ***
DESTIN_GRID_ID2280 -1.5569256 0.0658152 -23.656 < 2e-16 ***
DESTIN_GRID_ID2297 -1.5184772 0.0597673 -25.406 < 2e-16 ***
DESTIN_GRID_ID2300 -1.1998356 0.0598378 -20.051 < 2e-16 ***
DESTIN_GRID_ID2301 -0.5110001 0.0569116 -8.979 < 2e-16 ***
DESTIN_GRID_ID2318 0.8554331 0.0562907 15.197 < 2e-16 ***
DESTIN_GRID_ID2319 0.7850917 0.0562766 13.951 < 2e-16 ***
DESTIN_GRID_ID2322 -0.2299003 0.0569045 -4.040 5.34e-05 ***
DESTIN_GRID_ID2337 0.1741154 0.0597446 2.914 0.003565 **
DESTIN_GRID_ID2341 1.0063818 0.0562634 17.887 < 2e-16 ***
DESTIN_GRID_ID2343 -1.0924958 0.0577950 -18.903 < 2e-16 ***
DESTIN_GRID_ID2361 -0.2502748 0.0568730 -4.401 1.08e-05 ***
DESTIN_GRID_ID2364 -2.3202217 0.0667959 -34.736 < 2e-16 ***
DESTIN_GRID_ID2379 -1.0452739 0.0630891 -16.568 < 2e-16 ***
DESTIN_GRID_ID2384 0.8460054 0.0564245 14.994 < 2e-16 ***
DESTIN_GRID_ID2405 1.6191473 0.0562189 28.801 < 2e-16 ***
DESTIN_GRID_ID2406 -1.4130374 0.0610447 -23.148 < 2e-16 ***
DESTIN_GRID_ID2426 1.0424775 0.0571466 18.242 < 2e-16 ***
DESTIN_GRID_ID2427 1.3086936 0.0564288 23.192 < 2e-16 ***
DESTIN_GRID_ID2505 0.7641516 0.0596898 12.802 < 2e-16 ***
log(dist) -1.5794583 0.0003209 -4921.781 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 80934257 on 62183 degrees of freedom
Residual deviance: 20701997 on 60549 degrees of freedom
AIC: 21041345
Number of Fisher Scoring iterations: 9Conclusion and limitations
Four Spatial Interaction Models were built and compared to find out the important factors influencing the commuter flow in the Weekday Morning peak period. The R-squared values for the UNC, ORC, DEC and DBC models are 0.25, 0.38, 0.37 and 0.58 respectively. From the UNC and ORC models, the significant factors affecting commuter flow are distance (negative relationship), destination MRT station exits count and destination school count (in order of highest influence first). From the DEC model, the significant factors are distance and origin 5room flat dwellers count.
When the outliers were removed, the R-squared value of the new DBC model increased to 0.60. Possible reason why the model could not predict flow of bus stops near Woodlands Checkpoint region could be that the number of people commuting between JB and Singapore daily for work purpose is really too huge and concentrated over Woodlands. We are also lacking the work opportunities information in JB side for model to predict properly.
With the models created, possible ‘what-if’ scenarios can be simulated; take for instance what if there are new MRT stations / development of a new residential town in the future? The models could predict new flows patterns and assist transport authority to plan ahead.
Limitations of this exercise would include:
- The Passenger Volume by Origin Destination Bus Stops data used does not include any transfer trip information. With our attractive and propulsive attributes, we can only assume that passengers take only 1 bus trip from source to their intended destination. With the inclusion of the MRT train station exits locations, we factor in the possibility of passenger commuting to MRT station for transfer.
- The population density distribution of Residents could only be estimated from the HDB.csv and not directly taken from the Resident Distribution by single age and subzone dataset because we have reduced our basic spatial unit to 750m hexagons instead of subzone (to reduce social-economic and spatial aggregation errors). Now, each hexagon could have a mix of 7 subzones inside it, thus use of Resident Distribution by single age and subzone dataset is inappropriate (otherwise we could have achieved better results).
Acknowledgement
I would like to extend my heartfelt gratitude to Prof Kam for being an exceptional instructor and mentor throughout all his courses that I have attended. His dedication, patience, and generosity in sharing knowledge have made a profound impact on my MITB journey. Thank you!
References
Tin Seong Kam. “2 Choropleth Mapping with R” From R for Geospatial Data Science and Analytics https://r4gdsa.netlify.app/chap02
Tin Seong Kam. “15 Processing and Visualszing Flow Data” From R for Geospatial Data Science and Analytics https://r4gdsa.netlify.app/chap15
Tin Seong Kam. “In-Class Exercise 4: Preparing Spatial Interaction Modelling Variables” https://isss624.netlify.app/in-class_ex/in-class_ex4/in-class_ex4-gds#data-integration-and-final-touch-up